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\n  \n 2024\n \n \n (6)\n \n \n
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\n \n\n \n \n \n \n \n DualAttNet: Synergistic fusion of image-level and fine-grained disease attention for multi-label lesion detection in chest X-rays.\n \n \n \n\n\n \n Xu, Q.; and Duan, W.\n\n\n \n\n\n\n Computers in Biology and Medicine, 168: 107742. 2024.\n \n\n\n\n
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@article{xu2024dualattnet,\n  title={DualAttNet: Synergistic fusion of image-level and fine-grained disease attention for multi-label lesion detection in chest X-rays},\n  author={Xu, Qing and Duan, Wenting},\n  journal={Computers in Biology and Medicine},\n  volume={168},\n  pages={107742},\n  year={2024},\n  publisher={Pergamon}\n}\n\n
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\n \n\n \n \n \n \n \n Revisiting the Problem of Missing Values in High-Dimensional Data and Feature Selection Effect.\n \n \n \n\n\n \n Elia, M. G; and Duan, W.\n\n\n \n\n\n\n In IFIP International Conference on Artificial Intelligence Applications and Innovations, pages 201–213, 2024. Springer Nature Switzerland Cham\n \n\n\n\n
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@inproceedings{elia2024revisiting,\n  title={Revisiting the Problem of Missing Values in High-Dimensional Data and Feature Selection Effect},\n  author={Elia, Marina G and Duan, Wenting},\n  booktitle={IFIP International Conference on Artificial Intelligence Applications and Innovations},\n  pages={201--213},\n  year={2024},\n  organization={Springer Nature Switzerland Cham}\n}\n\n
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\n \n\n \n \n \n \n \n ESP-MedSAM: Efficient Self-Prompting SAM for Universal Domain-Generalized Medical Image Segmentation.\n \n \n \n\n\n \n Xu, Q.; Li, J.; He, X.; Liu, Z.; Chen, Z.; Duan, W.; Li, C.; He, M. M; Tesema, F. B; Cheah, W. P; and others\n\n\n \n\n\n\n arXiv preprint arXiv:2407.14153. 2024.\n \n\n\n\n
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@article{xu2024esp,\n  title={ESP-MedSAM: Efficient Self-Prompting SAM for Universal Domain-Generalized Medical Image Segmentation},\n  author={Xu, Qing and Li, Jiaxuan and He, Xiangjian and Liu, Ziyu and Chen, Zhen and Duan, Wenting and Li, Chenxin and He, Maggie M and Tesema, Fiseha B and Cheah, Wooi P and others},\n  journal={arXiv preprint arXiv:2407.14153},\n  year={2024}\n}\n\n
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\n \n\n \n \n \n \n \n NuSegDG: Integration of Heterogeneous Space and Gaussian Kernel for Domain-Generalized Nuclei Segmentation.\n \n \n \n\n\n \n Lou, Z.; Xu, Q.; Jiang, Z.; He, X.; Chen, Z.; Wang, Y.; Li, C.; He, M. M; and Duan, W.\n\n\n \n\n\n\n arXiv preprint arXiv:2408.11787. 2024.\n \n\n\n\n
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@article{lou2024nusegdg,\n  title={NuSegDG: Integration of Heterogeneous Space and Gaussian Kernel for Domain-Generalized Nuclei Segmentation},\n  author={Lou, Zhenye and Xu, Qing and Jiang, Zekun and He, Xiangjian and Chen, Zhen and Wang, Yi and Li, Chenxin and He, Maggie M and Duan, Wenting},\n  journal={arXiv preprint arXiv:2408.11787},\n  year={2024}\n}\n\n
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\n \n\n \n \n \n \n \n Pushing the limits of cell segmentation models for imaging mass cytometry.\n \n \n \n\n\n \n Bird, K. M; Ye, X.; Race, A. M; and Brown, J. M\n\n\n \n\n\n\n arXiv preprint arXiv:2402.04446. 2024.\n \n\n\n\n
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@article{bird2024pushing,\n  title={Pushing the limits of cell segmentation models for imaging mass cytometry},\n  author={Bird, Kimberley M and Ye, Xujiong and Race, Alan M and Brown, James M},\n  journal={arXiv preprint arXiv:2402.04446},\n  year={2024}\n}\n\n
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\n \n\n \n \n \n \n \n Hierarchical Multi-label Learning for Musculoskeletal Phenotyping in Mice.\n \n \n \n\n\n \n Jawaid, M. M.; Bains, S. R.; Wells, S.; and Brown, J. M\n\n\n \n\n\n\n In Annual Conference on Medical Image Understanding and Analysis, pages 425–437, 2024. Springer\n \n\n\n\n
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@inproceedings{jawaid2024hierarchical,\n  title={Hierarchical Multi-label Learning for Musculoskeletal Phenotyping in Mice},\n  author={Jawaid, Muhammad Moazzam and Bains, Sonia Rasneer and Wells, Sara and Brown, James M},\n  booktitle={Annual Conference on Medical Image Understanding and Analysis},\n  pages={425--437},\n  year={2024},\n  organization={Springer}\n}\n
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\n  \n 2023\n \n \n (12)\n \n \n
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\n \n\n \n \n \n \n \n Domain generalised fully convolutional one stage detection.\n \n \n \n\n\n \n Seemakurthy, K.; Bosilj, P.; Aptoula, E.; and Fox, C.\n\n\n \n\n\n\n In 2023 IEEE International Conference on Robotics and Automation (ICRA), pages 7002–7009, 2023. IEEE\n \n\n\n\n
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@inproceedings{seemakurthy2023domain,\n  title={Domain generalised fully convolutional one stage detection},\n  author={Seemakurthy, Karthik and Bosilj, Petra and Aptoula, Erchan and Fox, Charles},\n  booktitle={2023 IEEE International Conference on Robotics and Automation (ICRA)},\n  pages={7002--7009},\n  year={2023},\n  organization={IEEE}\n}\n\n
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\n \n\n \n \n \n \n \n Domain generalised faster R-CNN.\n \n \n \n\n\n \n Seemakurthy, K.; Fox, C.; Aptoula, E.; and Bosilj, P.\n\n\n \n\n\n\n In Proceedings of the AAAI Conference on Artificial Intelligence, volume 37, pages 2180–2190, 2023. \n \n\n\n\n
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@inproceedings{seemakurthy2023domain,\n  title={Domain generalised faster R-CNN},\n  author={Seemakurthy, Karthik and Fox, Charles and Aptoula, Erchan and Bosilj, Petra},\n  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},\n  volume={37},\n  number={2},\n  pages={2180--2190},\n  year={2023}\n}\n\n
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\n \n\n \n \n \n \n \n An assessment of self-supervised learning for data efficient potato instance segmentation.\n \n \n \n\n\n \n Hurst, B.; Bellotto, N.; and Bosilj, P.\n\n\n \n\n\n\n In Annual Conference Towards Autonomous Robotic Systems, pages 267–278, 2023. Springer Nature Switzerland Cham\n \n\n\n\n
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@inproceedings{hurst2023assessment,\n  title={An assessment of self-supervised learning for data efficient potato instance segmentation},\n  author={Hurst, Bradley and Bellotto, Nicola and Bosilj, Petra},\n  booktitle={Annual Conference Towards Autonomous Robotic Systems},\n  pages={267--278},\n  year={2023},\n  organization={Springer Nature Switzerland Cham}\n}\n\n
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\n \n\n \n \n \n \n \n DCSAU-Net: A deeper and more compact split-attention U-Net for medical image segmentation.\n \n \n \n\n\n \n Xu, Q.; Ma, Z.; Na, H.; and Duan, W.\n\n\n \n\n\n\n Computers in Biology and Medicine, 154: 106626. 2023.\n \n\n\n\n
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@article{xu2023dcsau,\n  title={DCSAU-Net: A deeper and more compact split-attention U-Net for medical image segmentation},\n  author={Xu, Qing and Ma, Zhicheng and Na, HE and Duan, Wenting},\n  journal={Computers in Biology and Medicine},\n  volume={154},\n  pages={106626},\n  year={2023},\n  publisher={Pergamon}\n}\n\n
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\n \n\n \n \n \n \n \n Sppnet: A single-point prompt network for nuclei image segmentation.\n \n \n \n\n\n \n Xu, Q.; Kuang, W.; Zhang, Z.; Bao, X.; Chen, H.; and Duan, W.\n\n\n \n\n\n\n In International Workshop on Machine Learning in Medical Imaging, pages 227–236, 2023. Springer Nature Switzerland Cham\n \n\n\n\n
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@inproceedings{xu2023sppnet,\n  title={Sppnet: A single-point prompt network for nuclei image segmentation},\n  author={Xu, Qing and Kuang, Wenwei and Zhang, Zeyu and Bao, Xueyao and Chen, Haoran and Duan, Wenting},\n  booktitle={International Workshop on Machine Learning in Medical Imaging},\n  pages={227--236},\n  year={2023},\n  organization={Springer Nature Switzerland Cham}\n}\n\n
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\n \n\n \n \n \n \n \n MidFusNet: Mid-Dense Fusion Network for Multi-Modal Brain MRI Segmentation.\n \n \n \n\n\n \n Gulli, G.; Colman, J.; Duan, W.; Ye, X.; and Zhang, L.\n\n\n \n\n\n\n . 2023.\n \n\n\n\n
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@article{gulli2023midfusnet,\n  title={MidFusNet: Mid-Dense Fusion Network for Multi-Modal Brain MRI Segmentation},\n  author={Gulli, Giosue and Colman, Jordan and Duan, Wenting and Ye, Xujiong and Zhang, Lei},\n  year={2023},\n  publisher={University of Lincoln}\n}\n\n
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\n \n\n \n \n \n \n \n SPPNet: A Single-Point Prompt Network for Nuclei Image Segmentation.\n \n \n \n\n\n \n Chen, H.; Xu, Q.; Kuang, W. K.; Bao, X.; Zhang, Z.; and Duan, W.\n\n\n \n\n\n\n . 2023.\n \n\n\n\n
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@article{chen2023sppnet,\n  title={SPPNet: A Single-Point Prompt Network for Nuclei Image Segmentation},\n  author={Chen, Haoran and Xu, Qing and Kuang, Wenwei Kuang and Bao, Xueyao and Zhang, Zeyu and Duan, Wenting},\n  year={2023},\n  publisher={University of Lincoln}\n}\n\n
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\n \n\n \n \n \n \n \n Dual-stream spatiotemporal networks with feature sharing for monitoring animals in the home cage.\n \n \n \n\n\n \n Nwokedi, E. I.; Bains, R. S.; Bidaut, L.; Ye, X.; Wells, S.; and Brown, J. M\n\n\n \n\n\n\n Sensors, 23(23): 9532. 2023.\n \n\n\n\n
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@article{nwokedi2023dual,\n  title={Dual-stream spatiotemporal networks with feature sharing for monitoring animals in the home cage},\n  author={Nwokedi, Ezechukwu Israel and Bains, Rasneer Sonia and Bidaut, Luc and Ye, Xujiong and Wells, Sara and Brown, James M},\n  journal={Sensors},\n  volume={23},\n  number={23},\n  pages={9532},\n  year={2023},\n  publisher={MDPI}\n}\n\n
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\n \n\n \n \n \n \n \n DeepVerge: Classification of roadside verge biodiversity and conservation potential.\n \n \n \n\n\n \n Perrett, A.; Pollard, H.; Barnes, C.; Schofield, M.; Qie, L.; Bosilj, P.; and Brown, J. M\n\n\n \n\n\n\n Computers, Environment and Urban Systems, 102: 101968. 2023.\n \n\n\n\n
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@article{perrett2023deepverge,\n  title={DeepVerge: Classification of roadside verge biodiversity and conservation potential},\n  author={Perrett, Andrew and Pollard, Harry and Barnes, Charlie and Schofield, Mark and Qie, Lan and Bosilj, Petra and Brown, James M},\n  journal={Computers, Environment and Urban Systems},\n  volume={102},\n  pages={101968},\n  year={2023},\n  publisher={Pergamon}\n}\n\n
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\n \n\n \n \n \n \n \n Association of biomarker-based artificial intelligence with risk of racial bias in retinal images.\n \n \n \n\n\n \n Coyner, A. S; Singh, P.; Brown, J. M; Ostmo, S.; Chan, R. P.; Chiang, M. F; Kalpathy-Cramer, J.; Campbell, J P.; Young, B. K; Sang Jin, K.; and others\n\n\n \n\n\n\n JAMA ophthalmology, 141(6): 543–552. 2023.\n \n\n\n\n
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@article{coyner2023association,\n  title={Association of biomarker-based artificial intelligence with risk of racial bias in retinal images},\n  author={Coyner, Aaron S and Singh, Praveer and Brown, James M and Ostmo, Susan and Chan, RV Paul and Chiang, Michael F and Kalpathy-Cramer, Jayashree and Campbell, J Peter and Young, Benjamin K and Sang Jin, Kim and others},\n  journal={JAMA ophthalmology},\n  volume={141},\n  number={6},\n  pages={543--552},\n  year={2023},\n  publisher={American Medical Association}\n}\n\n
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\n \n\n \n \n \n \n \n Bavituximab decreases immunosuppressive myeloid-derived suppressor cells in newly diagnosed glioblastoma patients.\n \n \n \n\n\n \n Ly, K I.; Richardson, L. G; Liu, M.; Muzikansky, A.; Cardona, J.; Lou, K.; Beers, A. L; Chang, K.; Brown, J. M; Ma, X.; and others\n\n\n \n\n\n\n Clinical Cancer Research, 29(16): 3017–3025. 2023.\n \n\n\n\n
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@article{ly2023bavituximab,\n  title={Bavituximab decreases immunosuppressive myeloid-derived suppressor cells in newly diagnosed glioblastoma patients},\n  author={Ly, K Ina and Richardson, Leland G and Liu, Mofei and Muzikansky, Alona and Cardona, Jonathan and Lou, Kevin and Beers, Andrew L and Chang, Ken and Brown, James M and Ma, Xiaoyue and others},\n  journal={Clinical Cancer Research},\n  volume={29},\n  number={16},\n  pages={3017--3025},\n  year={2023},\n  publisher={American Association for Cancer Research}\n}\n\n
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\n \n\n \n \n \n \n \n Weakly Supervised Pre-Training for Brain Tumour Segmentation Using Principal Axis Measurements of Tumour Burden.\n \n \n \n\n\n \n Mckone, J. E.; Lambrou, T.; Ye, X.; and Brown, J.\n\n\n \n\n\n\n Available at SSRN 4435323. 2023.\n \n\n\n\n
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@article{mckone2023weakly,\n  title={Weakly Supervised Pre-Training for Brain Tumour Segmentation Using Principal Axis Measurements of Tumour Burden},\n  author={Mckone, Joshua Edward and Lambrou, Tryphon and Ye, Xujiong and Brown, James},\n  journal={Available at SSRN 4435323},\n  year={2023}\n}\n\n
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\n \n\n \n \n \n \n \n Domain Generalisation for Object Detection under Covariate and Concept Shift.\n \n \n \n\n\n \n Seemakurthy, K.; Aptoula, E.; Fox, C.; and Bosilj, P.\n\n\n \n\n\n\n arXiv preprint arXiv:2203.05294. 2022.\n \n\n\n\n
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@article{seemakurthy2022domain,\n  title={Domain Generalisation for Object Detection under Covariate and Concept Shift},\n  author={Seemakurthy, Karthik and Aptoula, Erchan and Fox, Charles and Bosilj, Petra},\n  journal={arXiv preprint arXiv:2203.05294},\n  year={2022}\n}\n\n
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\n \n\n \n \n \n \n \n AI-enabled Safe and Efficient Food Supply Chain.\n \n \n \n\n\n \n Kollias, S.; Ye, X.; Yu, M.; Duan, W.; Leontidis, G.; Swainson, M.; and Pearson, S.\n\n\n \n\n\n\n . 2022.\n \n\n\n\n
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@article{kollias2022ai,\n  title={AI-enabled Safe and Efficient Food Supply Chain},\n  author={Kollias, Stefanos and Ye, Xujiong and Yu, Miao and Duan, Wenting and Leontidis, Georgios and Swainson, Mark and Pearson, Simon},\n  year={2022},\n  publisher={Research Excellence Framework (REF) 2021}\n}\n\n
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\n \n\n \n \n \n \n \n MidFusNet: Mid-dense Fusion Network for Multi-modal Brain MRI Segmentation.\n \n \n \n\n\n \n Duan, W.; Zhang, L.; Colman, J.; Gulli, G.; and Ye, X.\n\n\n \n\n\n\n In International MICCAI Brainlesion Workshop, pages 102–114, 2022. Springer Nature Switzerland Cham\n \n\n\n\n
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@inproceedings{duan2022midfusnet,\n  title={MidFusNet: Mid-dense Fusion Network for Multi-modal Brain MRI Segmentation},\n  author={Duan, Wenting and Zhang, Lei and Colman, Jordan and Gulli, Giosue and Ye, Xujiong},\n  booktitle={International MICCAI Brainlesion Workshop},\n  pages={102--114},\n  year={2022},\n  organization={Springer Nature Switzerland Cham}\n}\n\n
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\n \n\n \n \n \n \n \n Federated learning for multicenter collaboration in ophthalmology: implications for clinical diagnosis and disease epidemiology.\n \n \n \n\n\n \n Hanif, A.; Lu, C.; Chang, K.; Singh, P.; Coyner, A. S; Brown, J. M; Ostmo, S.; Chan, R. V P.; Rubin, D.; Chiang, M. F; and others\n\n\n \n\n\n\n Ophthalmology Retina, 6(8): 650–656. 2022.\n \n\n\n\n
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@article{hanif2022federated,\n  title={Federated learning for multicenter collaboration in ophthalmology: implications for clinical diagnosis and disease epidemiology},\n  author={Hanif, Adam and Lu, Charles and Chang, Ken and Singh, Praveer and Coyner, Aaron S and Brown, James M and Ostmo, Susan and Chan, Robison V Paul and Rubin, Daniel and Chiang, Michael F and others},\n  journal={Ophthalmology Retina},\n  volume={6},\n  number={8},\n  pages={650--656},\n  year={2022},\n  publisher={Elsevier}\n}\n\n
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\n \n\n \n \n \n \n \n Federated learning for multicenter collaboration in ophthalmology: improving classification performance in retinopathy of prematurity.\n \n \n \n\n\n \n Lu, C.; Hanif, A.; Singh, P.; Chang, K.; Coyner, A. S; Brown, J. M; Ostmo, S.; Chan, R. V P.; Rubin, D.; Chiang, M. F; and others\n\n\n \n\n\n\n Ophthalmology Retina, 6(8): 657–663. 2022.\n \n\n\n\n
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@article{lu2022federated,\n  title={Federated learning for multicenter collaboration in ophthalmology: improving classification performance in retinopathy of prematurity},\n  author={Lu, Charles and Hanif, Adam and Singh, Praveer and Chang, Ken and Coyner, Aaron S and Brown, James M and Ostmo, Susan and Chan, Robison V Paul and Rubin, Daniel and Chiang, Michael F and others},\n  journal={Ophthalmology Retina},\n  volume={6},\n  number={8},\n  pages={657--663},\n  year={2022},\n  publisher={Elsevier}\n}\n\n
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@article{gomez2021deep,\n  title={Deep regression versus detection for counting in robotic phenotyping},\n  author={Gomez, Adrian Salazar and Aptoula, Erchan and Parsons, Simon and Bosilj, Petra},\n  journal={IEEE Robotics and Automation Letters},\n  volume={6},\n  number={2},\n  pages={2902--2907},\n  year={2021},\n  publisher={IEEE}\n}\n\n
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@article{gong2021novel,\n  title={A novel unified deep neural networks methodology for use by date recognition in retail food package image},\n  author={Gong, Liyun and Thota, Mamatha and Yu, Miao and Duan, Wenting and Swainson, Mark and Ye, Xujiong and Kollias, Stefanos},\n  journal={Signal, Image and Video Processing},\n  volume={15},\n  pages={449--457},\n  year={2021},\n  publisher={Springer London}\n}\n\n
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\n \n\n \n \n \n \n \n DR-Unet104 for Multimodal MRI brain tumor segmentation.\n \n \n \n\n\n \n Colman, J.; Zhang, L.; Duan, W.; and Ye, X.\n\n\n \n\n\n\n In Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries: 6th International Workshop, BrainLes 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Revised Selected Papers, Part II 6, pages 410–419, 2021. Springer International Publishing\n \n\n\n\n
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@inproceedings{colman2021dr,\n  title={DR-Unet104 for Multimodal MRI brain tumor segmentation},\n  author={Colman, Jordan and Zhang, Lei and Duan, Wenting and Ye, Xujiong},\n  booktitle={Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries: 6th International Workshop, BrainLes 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Revised Selected Papers, Part II 6},\n  pages={410--419},\n  year={2021},\n  organization={Springer International Publishing}\n}\n\n
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\n \n\n \n \n \n \n \n Mid-Dense Fusion Network for Multi-Modal Brain MRI Segmentation.\n \n \n \n\n\n \n Duan, W.; Colman, J.; Zhang, L.; Gulli, G.; and Ye, X.\n\n\n \n\n\n\n . 2021.\n \n\n\n\n
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@article{duan2021mid,\n  title={Mid-Dense Fusion Network for Multi-Modal Brain MRI Segmentation},\n  author={Duan, Wenting and Colman, Jordan and Zhang, Lei and Gulli, Giosue and Ye, Xujiong},\n  year={2021}\n}\n\n
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@inproceedings{hua2021investigating,\n  title={Investigating Refractoriness in Collision Perception Neuronal Model},\n  author={Hua, Mu and Fu, Qinbing and Duan, Wenting and Yue, Shigang},\n  booktitle={2021 International Joint Conference on Neural Networks (IJCNN)},\n  pages={1--8},\n  year={2021},\n  organization={IEEE}\n}\n\n
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@inproceedings{xu2021automatic,\n  title={An automatic nuclei image segmentation based on multi-scale split-attention U-Net},\n  author={Xu, Qing and Duan, Wenting},\n  booktitle={MICCAI Workshop on Computational Pathology},\n  pages={236--245},\n  year={2021},\n  organization={PMLR}\n}\n\n
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\n \n\n \n \n \n \n \n Multi-modal brain segmentation using hyper-fused convolutional neural network.\n \n \n \n\n\n \n Duan, W.; Zhang, L.; Colman, J.; Gulli, G.; and Ye, X.\n\n\n \n\n\n\n In Machine Learning in Clinical Neuroimaging: 4th International Workshop, MLCN 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings 4, pages 82–91, 2021. Springer International Publishing\n \n\n\n\n
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@inproceedings{duan2021multi,\n  title={Multi-modal brain segmentation using hyper-fused convolutional neural network},\n  author={Duan, Wenting and Zhang, Lei and Colman, Jordan and Gulli, Giosue and Ye, Xujiong},\n  booktitle={Machine Learning in Clinical Neuroimaging: 4th International Workshop, MLCN 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings 4},\n  pages={82--91},\n  year={2021},\n  organization={Springer International Publishing}\n}\n\n
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\n \n\n \n \n \n \n \n Multi-Modal Brain Segmentation Using Hyper-Fused Convolutional Neural Network.\n \n \n \n\n\n \n Gulli, G.; Colman, J.; Duan, W.; Ye, X.; and Zhang, L.\n\n\n \n\n\n\n . 2021.\n \n\n\n\n
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@article{gulli2021multi,\n  title={Multi-Modal Brain Segmentation Using Hyper-Fused Convolutional Neural Network},\n  author={Gulli, Giosue and Colman, Jordan and Duan, Wenting and Ye, Xujiong and Zhang, Lei},\n  year={2021},\n  publisher={University of Lincoln}\n}\n\n
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\n \n\n \n \n \n \n \n LAMA: automated image analysis for the developmental phenotyping of mouse embryos.\n \n \n \n\n\n \n Horner, N. R; Venkataraman, S.; Armit, C.; Casero, R.; Brown, J. M; Wong, M. D; van Eede, M. C; Henkelman, R M.; Johnson, S.; Teboul, L.; and others\n\n\n \n\n\n\n Development, 148(18): dev192955. 2021.\n \n\n\n\n
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@article{horner2021lama,\n  title={LAMA: automated image analysis for the developmental phenotyping of mouse embryos},\n  author={Horner, Neil R and Venkataraman, Shanmugasundaram and Armit, Chris and Casero, Ram{\\'o}n and Brown, James M and Wong, Michael D and van Eede, Matthijs C and Henkelman, R Mark and Johnson, Sara and Teboul, Lydia and others},\n  journal={Development},\n  volume={148},\n  number={18},\n  pages={dev192955},\n  year={2021},\n  publisher={The Company of Biologists Ltd}\n}\n\n
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\n \n\n \n \n \n \n \n Evaluation of a Deep Learning–Derived Quantitative Retinopathy of Prematurity Severity Scale.\n \n \n \n\n\n \n Campbell, J P.; Kim, S. J.; Brown, J. M; Ostmo, S.; Chan, R. P.; Kalpathy-Cramer, J.; Chiang, M. F; Sonmez, K.; Schelonka, R.; Jonas, K.; and others\n\n\n \n\n\n\n Ophthalmology, 128(7): 1070–1076. 2021.\n \n\n\n\n
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@article{campbell2021evaluation,\n  title={Evaluation of a Deep Learning--Derived Quantitative Retinopathy of Prematurity Severity Scale},\n  author={Campbell, J Peter and Kim, Sang Jin and Brown, James M and Ostmo, Susan and Chan, RV Paul and Kalpathy-Cramer, Jayashree and Chiang, Michael F and Sonmez, Kemal and Schelonka, Robert and Jonas, Karyn and others},\n  journal={Ophthalmology},\n  volume={128},\n  number={7},\n  pages={1070--1076},\n  year={2021},\n  publisher={Elsevier}\n}\n\n
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\n \n\n \n \n \n \n \n Applications of artificial intelligence for retinopathy of prematurity screening.\n \n \n \n\n\n \n Campbell, J P.; Singh, P.; Redd, T. K; Brown, J. M; Shah, P. K; Subramanian, P.; Rajan, R.; Valikodath, N.; Cole, E.; Ostmo, S.; and others\n\n\n \n\n\n\n Pediatrics, 147(3). 2021.\n \n\n\n\n
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@article{campbell2021applications,\n  title={Applications of artificial intelligence for retinopathy of prematurity screening},\n  author={Campbell, J Peter and Singh, Praveer and Redd, Travis K and Brown, James M and Shah, Parag K and Subramanian, Prema and Rajan, Renu and Valikodath, Nita and Cole, Emily and Ostmo, Susan and others},\n  journal={Pediatrics},\n  volume={147},\n  number={3},\n  year={2021},\n  publisher={Am Acad Pediatrics}\n}\n\n
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@article{nwokedi2021unsupervised,\n  title={Unsupervised detection of mouse behavioural anomalies using two-stream convolutional autoencoders},\n  author={Nwokedi, Ezechukwu I and Bains, Rasneer S and Bidaut, Luc and Wells, Sara and Ye, Xujiong and Brown, James M},\n  journal={arXiv preprint arXiv:2106.00598},\n  year={2021}\n}\n\n
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@article{brown2021deep,\n  title={Deep learning for computer-aided diagnosis in ophthalmology: a review},\n  author={Brown, James M and Leontidis, Georgios},\n  journal={State of the Art in Neural Networks and their Applications},\n  pages={219--237},\n  year={2021},\n  publisher={Elsevier}\n}\n\n
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\n \n\n \n \n \n \n \n Not Color Blind: AI Predicts Racial Identity from Black and White Retinal Vessel Segmentations.\n \n \n \n\n\n \n Coyner, A. S; Singh, P.; Brown, J. M; Ostmo, S.; Chan, R.; Chiang, M. F; Kalpathy-Cramer, J.; and Campbell, J P.\n\n\n \n\n\n\n arXiv preprint arXiv:2109.13845. 2021.\n \n\n\n\n
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@article{coyner2021not,\n  title={Not Color Blind: AI Predicts Racial Identity from Black and White Retinal Vessel Segmentations},\n  author={Coyner, Aaron S and Singh, Praveer and Brown, James M and Ostmo, Susan and Chan, RV and Chiang, Michael F and Kalpathy-Cramer, Jayashree and Campbell, J Peter},\n  journal={arXiv preprint arXiv:2109.13845},\n  year={2021}\n}\n\n
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\n \n\n \n \n \n \n \n External validation of a deep learning algorithm for plus disease classification on a multinational ROP dataset.\n \n \n \n\n\n \n Singh, P.; Campbell, J P.; Ostmo, S.; Brown, J.; Hu, S.; Chaichaya, N.; Wongwai, P.; Asawaphureekorn, S.; Suwannaraj, S.; Morley, M.; and others\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 62(8): 3266–3266. 2021.\n \n\n\n\n
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@article{singh2021external,\n  title={External validation of a deep learning algorithm for plus disease classification on a multinational ROP dataset},\n  author={Singh, Praveer and Campbell, J Peter and Ostmo, Susan and Brown, James and Hu, Szu-Yeu and Chaichaya, Nathaphop and Wongwai, Phanthipha and Asawaphureekorn, Somkiat and Suwannaraj, Sirinya and Morley, Michael and others},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={62},\n  number={8},\n  pages={3266--3266},\n  year={2021},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Evaluation of a novel retinopathy of prematurity severity scale applied by clinicians and deep learning.\n \n \n \n\n\n \n Campbell, J P.; Kim, S. J.; Brown, J. M; Ostmo, S.; Chan, R. P.; Kalpathy-Cramer, J.; and Chiang, M. F\n\n\n \n\n\n\n Ophthalmology, 128(7): 1070. 2021.\n \n\n\n\n
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@article{campbell2021evaluation,\n  title={Evaluation of a novel retinopathy of prematurity severity scale applied by clinicians and deep learning},\n  author={Campbell, J Peter and Kim, Sang Jin and Brown, James M and Ostmo, Susan and Chan, RV Paul and Kalpathy-Cramer, Jayashree and Chiang, Michael F},\n  journal={Ophthalmology},\n  volume={128},\n  number={7},\n  pages={1070},\n  year={2021},\n  publisher={NIH Public Access}\n}\n\n
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@article{bosilj2020estimating,\n  title={Estimating soil aggregate size distribution from images using pattern spectra},\n  author={Bosilj, Petra and Gould, Iain and Duckett, Tom and Cielniak, Grzegorz},\n  journal={Biosystems Engineering},\n  volume={198},\n  pages={63--77},\n  year={2020},\n  publisher={Academic Press}\n}\n\n
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@article{beers2020deepneuro,\n  title={DeepNeuro: an open-source deep learning toolbox for neuroimaging},\n  author={Beers, Andrew and Brown, James and Chang, Ken and Hoebel, Katharina and Patel, Jay and Ly, K Ina and Tolaney, Sara M and Brastianos, Priscilla and Rosen, Bruce and Gerstner, Elizabeth R and others},\n  journal={Neuroinformatics},\n  pages={1--14},\n  year={2020},\n  publisher={Springer US}\n}\n\n
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\n \n\n \n \n \n \n \n Aggressive posterior retinopathy of prematurity: clinical and quantitative imaging features in a large North American Cohort.\n \n \n \n\n\n \n Bellsmith, K. N; Brown, J.; Kim, S. J.; Goldstein, I. H; Coyner, A.; Ostmo, S.; Gupta, K.; Chan, R. P.; Kalpathy-Cramer, J.; Chiang, M. F; and others\n\n\n \n\n\n\n Ophthalmology, 127(8): 1105–1112. 2020.\n \n\n\n\n
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@article{bellsmith2020aggressive,\n  title={Aggressive posterior retinopathy of prematurity: clinical and quantitative imaging features in a large North American Cohort},\n  author={Bellsmith, Kellyn N and Brown, James and Kim, Sang Jin and Goldstein, Isaac H and Coyner, Aaron and Ostmo, Susan and Gupta, Kishan and Chan, RV Paul and Kalpathy-Cramer, Jayashree and Chiang, Michael F and others},\n  journal={Ophthalmology},\n  volume={127},\n  number={8},\n  pages={1105--1112},\n  year={2020},\n  publisher={Elsevier}\n}\n\n
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\n \n\n \n \n \n \n \n Plus Disease in Retinopathy of Prematurity: Convolutional Neural Network Performance Using a Combined Neural Network and Feature Extraction Approach.\n \n \n \n\n\n \n Yildiz, V. M; Tian, P.; Yildiz, I.; Brown, J. M; Kalpathy-Cramer, J.; Dy, J.; Ioannidis, S.; Erdogmus, D.; Ostmo, S.; Kim, S. J.; and others\n\n\n \n\n\n\n Translational Vision Science & Technology, 9(2): 10–10. 2020.\n \n\n\n\n
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@article{yildiz2020plus,\n  title={Plus Disease in Retinopathy of Prematurity: Convolutional Neural Network Performance Using a Combined Neural Network and Feature Extraction Approach},\n  author={Yildiz, Veysi M and Tian, Peng and Yildiz, Ilkay and Brown, James M and Kalpathy-Cramer, Jayashree and Dy, Jennifer and Ioannidis, Stratis and Erdogmus, Deniz and Ostmo, Susan and Kim, Sang Jin and others},\n  journal={Translational Vision Science \\& Technology},\n  volume={9},\n  number={2},\n  pages={10--10},\n  year={2020},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging.\n \n \n \n\n\n \n Li, M. D; Chang, K.; Bearce, B.; Chang, C. Y; Huang, A. J; Campbell, J P.; Brown, J. M; Singh, P.; Hoebel, K. V; Erdoğmuş, D.; and others\n\n\n \n\n\n\n NPJ digital medicine, 3(1): 48. 2020.\n \n\n\n\n
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@article{li2020siamese,\n  title={Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging},\n  author={Li, Matthew D and Chang, Ken and Bearce, Ben and Chang, Connie Y and Huang, Ambrose J and Campbell, J Peter and Brown, James M and Singh, Praveer and Hoebel, Katharina V and Erdo{\\u{g}}mu{\\c{s}}, Deniz and others},\n  journal={NPJ digital medicine},\n  volume={3},\n  number={1},\n  pages={48},\n  year={2020},\n  publisher={Nature Publishing Group UK London}\n}\n\n
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\n \n\n \n \n \n \n \n Evaluation of artificial intelligence-based telemedicine screening for retinopathy of prematurity.\n \n \n \n\n\n \n Greenwald, M. F; Danford, I. D; Shahrawat, M.; Ostmo, S.; Brown, J.; Kalpathy-Cramer, J.; Bradshaw, K.; Schelonka, R.; Cohen, H. S; Chan, R. P.; and others\n\n\n \n\n\n\n Journal of American Association for Pediatric Ophthalmology and Strabismus. 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{greenwald2020evaluation,\n  title={Evaluation of artificial intelligence-based telemedicine screening for retinopathy of prematurity},\n  author={Greenwald, Miles F and Danford, Ian D and Shahrawat, Malika and Ostmo, Susan and Brown, James and Kalpathy-Cramer, Jayashree and Bradshaw, Kacy and Schelonka, Robert and Cohen, Howard S and Chan, RV Paul and others},\n  journal={Journal of American Association for Pediatric Ophthalmology and Strabismus},\n  year={2020},\n  publisher={Mosby}\n}\n\n
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\n \n\n \n \n \n \n \n Variability in Plus Disease Identified Using a Deep Learning-Based Retinopathy of Prematurity Severity Scale.\n \n \n \n\n\n \n Choi, R. Y; Brown, J. M; Kalpathy-Cramer, J.; Chan, R. P.; Ostmo, S.; Chiang, M. F; Campbell, J P.; Kim, S. J.; Sonmez, K.; Jonas, K.; and others\n\n\n \n\n\n\n Ophthalmology Retina, 4(10): 1016–1021. 2020.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{choi2020variability,\n  title={Variability in Plus Disease Identified Using a Deep Learning-Based Retinopathy of Prematurity Severity Scale},\n  author={Choi, Rene Y and Brown, James M and Kalpathy-Cramer, Jayashree and Chan, RV Paul and Ostmo, Susan and Chiang, Michael F and Campbell, J Peter and Kim, Sang Jin and Sonmez, Kemal and Jonas, Karyn and others},\n  journal={Ophthalmology Retina},\n  volume={4},\n  number={10},\n  pages={1016--1021},\n  year={2020},\n  publisher={Elsevier}\n}\n\n
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\n \n\n \n \n \n \n \n Radiomics repeatability pitfalls in a scan-rescan MRI study of glioblastoma.\n \n \n \n\n\n \n Hoebel, K. V; Patel, J. B; Beers, A. L; Chang, K.; Singh, P.; Brown, J. M; Pinho, M. C; Batchelor, T. T; Gerstner, E. R; Rosen, B. R; and others\n\n\n \n\n\n\n Radiology: Artificial Intelligence, 3(1): e190199. 2020.\n \n\n\n\n
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@article{hoebel2020radiomics,\n  title={Radiomics repeatability pitfalls in a scan-rescan MRI study of glioblastoma},\n  author={Hoebel, Katharina V and Patel, Jay B and Beers, Andrew L and Chang, Ken and Singh, Praveer and Brown, James M and Pinho, Marco C and Batchelor, Tracy T and Gerstner, Elizabeth R and Rosen, Bruce R and others},\n  journal={Radiology: Artificial Intelligence},\n  volume={3},\n  number={1},\n  pages={e190199},\n  year={2020},\n  publisher={Radiological Society of North America}\n}\n\n
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\n  \n 2019\n \n \n (24)\n \n \n
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\n \n\n \n \n \n \n \n Transfer learning between crop types for semantic segmentation of crops versus weeds in precision agriculture.\n \n \n \n\n\n \n Bosilj, P.; Aptoula, E.; Duckett, T.; and Cielniak, G.\n\n\n \n\n\n\n Journal of Field Robotics. 2019.\n \n\n\n\n
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@article{bosilj2019transfer,\n  title={Transfer learning between crop types for semantic segmentation of crops versus weeds in precision agriculture},\n  author={Bosilj, Petra and Aptoula, Erchan and Duckett, Tom and Cielniak, Grzegorz},\n  journal={Journal of Field Robotics},\n  year={2019},\n  publisher={Wiley Online Library}\n}\n\n
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\n \n\n \n \n \n \n \n Evaluation of a deep learning image assessment system for detecting severe retinopathy of prematurity.\n \n \n \n\n\n \n Redd, T. K; Campbell, J. P.; Brown, J. M; Kim, S. J.; Ostmo, S.; Chan, R. V. P.; Dy, J.; Erdogmus, D.; Ioannidis, S.; Kalpathy-Cramer, J.; and others\n\n\n \n\n\n\n British Journal of Ophthalmology, 103(5): 580–584. 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{redd2019evaluation,\n  title={Evaluation of a deep learning image assessment system for detecting severe retinopathy of prematurity},\n  author={Redd, Travis K and Campbell, John Peter and Brown, James M and Kim, Sang Jin and Ostmo, Susan and Chan, Robison Vernon Paul and Dy, Jennifer and Erdogmus, Deniz and Ioannidis, Stratis and Kalpathy-Cramer, Jayashree and others},\n  journal={British Journal of Ophthalmology},\n  volume={103},\n  number={5},\n  pages={580--584},\n  year={2019},\n  publisher={BMJ Publishing Group Ltd}\n}\n\n
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\n \n\n \n \n \n \n \n Automated fundus image quality assessment in retinopathy of prematurity using deep convolutional neural networks.\n \n \n \n\n\n \n Coyner, A. S; Swan, R.; Campbell, J P.; Ostmo, S.; Brown, J. M; Kalpathy-Cramer, J.; Kim, S. J.; Jonas, K. E; Chan, R. P.; Chiang, M. F; and others\n\n\n \n\n\n\n Ophthalmology Retina, 3(5): 444–450. 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{coyner2019automated,\n  title={Automated fundus image quality assessment in retinopathy of prematurity using deep convolutional neural networks},\n  author={Coyner, Aaron S and Swan, Ryan and Campbell, J Peter and Ostmo, Susan and Brown, James M and Kalpathy-Cramer, Jayashree and Kim, Sang Jin and Jonas, Karyn E and Chan, RV Paul and Chiang, Michael F and others},\n  journal={Ophthalmology Retina},\n  volume={3},\n  number={5},\n  pages={444--450},\n  year={2019},\n  publisher={Elsevier}\n}\n\n
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\n \n\n \n \n \n \n \n CaRENets: Compact and Resource-Efficient CNN for Homomorphic Inference on Encrypted Medical Images.\n \n \n \n\n\n \n Chao, J.; Badawi, A. A.; Unnikrishnan, B.; Lin, J.; Mun, C. F.; Brown, J. M; Campbell, J P.; Chiang, M.; Kalpathy-Cramer, J.; Chandrasekhar, V. R.; and others\n\n\n \n\n\n\n arXiv preprint arXiv:1901.10074. 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{chao2019carenets,\n  title={CaRENets: Compact and Resource-Efficient CNN for Homomorphic Inference on Encrypted Medical Images},\n  author={Chao, Jin and Badawi, Ahmad Al and Unnikrishnan, Balagopal and Lin, Jie and Mun, Chan Fook and Brown, James M and Campbell, J Peter and Chiang, Michael and Kalpathy-Cramer, Jayashree and Chandrasekhar, Vijay Ramaseshan and others},\n  journal={arXiv preprint arXiv:1901.10074},\n  year={2019}\n}\n\n
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\n \n\n \n \n \n \n \n Viscerotoxic Brain Infarcts: The Results of Heart-Brain Interactions Study.\n \n \n \n\n\n \n Chang, K.; Brown, J.; Beers, A.; Kalpathy-Cramer, J.; and Ay, H.\n\n\n \n\n\n\n Stroke, 50(Suppl_1): A162–A162. 2019.\n \n\n\n\n
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@article{chang2019viscerotoxic,\n  title={Viscerotoxic Brain Infarcts: The Results of Heart-Brain Interactions Study},\n  author={Chang, Ken and Brown, James and Beers, Andrew and Kalpathy-Cramer, Jayashree and Ay, Hakan},\n  journal={Stroke},\n  volume={50},\n  number={Suppl\\_1},\n  pages={A162--A162},\n  year={2019},\n  publisher={Am Heart Assoc}\n}\n\n
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\n \n\n \n \n \n \n \n Improved interpretability for computer-aided severity assessment of retinopathy of prematurity.\n \n \n \n\n\n \n Graziani, M.; Brown, J. M; Andrearczyk, V.; Yildiz, V.; Campbell, J P.; Erdogmus, D.; Ioannidis, S.; Chiang, M. F; Kalpathy-Cramer, J.; and Müller, H.\n\n\n \n\n\n\n In Medical Imaging 2019: Computer-Aided Diagnosis, volume 10950, pages 450–460, 2019. SPIE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{graziani2019improved,\n  title={Improved interpretability for computer-aided severity assessment of retinopathy of prematurity},\n  author={Graziani, Mara and Brown, James M and Andrearczyk, Vincent and Yildiz, Veysi and Campbell, J Peter and Erdogmus, Deniz and Ioannidis, Stratis and Chiang, Michael F and Kalpathy-Cramer, Jayashree and M{\\"u}ller, Henning},\n  booktitle={Medical Imaging 2019: Computer-Aided Diagnosis},\n  volume={10950},\n  pages={450--460},\n  year={2019},\n  organization={SPIE}\n}\n\n
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\n \n\n \n \n \n \n \n MRI changes in patients with newly diagnosed glioblastoma treated as part of a Phase II trial with bavituximab, radiation, and temozolomide (P1. 6-003).\n \n \n \n\n\n \n Ly, I.; Cardona, J.; Beers, A.; Chang, K.; Brown, J.; Reardon, D.; Arrillaga-Romany, I.; Dietrich, J.; Forst, D.; Lee, E.; and others\n\n\n \n\n\n\n 2019.\n \n\n\n\n
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@misc{ly2019mri,\n  title={MRI changes in patients with newly diagnosed glioblastoma treated as part of a Phase II trial with bavituximab, radiation, and temozolomide (P1. 6-003)},\n  author={Ly, Ina and Cardona, Jonathan and Beers, Andrew and Chang, Ken and Brown, James and Reardon, David and Arrillaga-Romany, Isabel and Dietrich, Jorg and Forst, Deborah and Lee, Eudocia and others},\n  year={2019},\n  publisher={Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology}\n}\n\n
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\n \n\n \n \n \n \n \n Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement.\n \n \n \n\n\n \n Chang, K.; Beers, A. L; Bai, H. X; Brown, J. M; Ly, K I.; Li, X.; Senders, J. T; Kavouridis, V. K; Boaro, A.; Su, C.; and others\n\n\n \n\n\n\n Neuro-oncology, 21(11): 1412–1422. 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{chang2019automatic,\n  title={Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement},\n  author={Chang, Ken and Beers, Andrew L and Bai, Harrison X and Brown, James M and Ly, K Ina and Li, Xuejun and Senders, Joeky T and Kavouridis, Vasileios K and Boaro, Alessandro and Su, Chang and others},\n  journal={Neuro-oncology},\n  volume={21},\n  number={11},\n  pages={1412--1422},\n  year={2019},\n  publisher={Oxford University Press US}\n}\n\n
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\n \n\n \n \n \n \n \n Classification and comparison via neural networks.\n \n \n \n\n\n \n Yıldız, İ.; Tian, P.; Dy, J.; Erdoğmuş, D.; Brown, J.; Kalpathy-Cramer, J.; Ostmo, S.; Campbell, J P.; Chiang, M. F; and Ioannidis, S.\n\n\n \n\n\n\n Neural Networks, 118: 65–80. 2019.\n \n\n\n\n
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@article{yildiz2019classification,\n  title={Classification and comparison via neural networks},\n  author={Y{\\i}ld{\\i}z, {\\.I}lkay and Tian, Peng and Dy, Jennifer and Erdo{\\u{g}}mu{\\c{s}}, Deniz and Brown, James and Kalpathy-Cramer, Jayashree and Ostmo, Susan and Campbell, J Peter and Chiang, Michael F and Ioannidis, Stratis},\n  journal={Neural Networks},\n  volume={118},\n  pages={65--80},\n  year={2019},\n  publisher={Pergamon}\n}\n\n
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\n \n\n \n \n \n \n \n Monitoring disease progression with a quantitative severity scale for retinopathy of prematurity using deep learning.\n \n \n \n\n\n \n Taylor, S.; Brown, J. M; Gupta, K.; Campbell, J P.; Ostmo, S.; Chan, R. P.; Dy, J.; Erdogmus, D.; Ioannidis, S.; Kim, S. J; and others\n\n\n \n\n\n\n JAMA ophthalmology, 137(9): 1022–1028. 2019.\n \n\n\n\n
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@article{taylor2019monitoring,\n  title={Monitoring disease progression with a quantitative severity scale for retinopathy of prematurity using deep learning},\n  author={Taylor, Stanford and Brown, James M and Gupta, Kishan and Campbell, J Peter and Ostmo, Susan and Chan, RV Paul and Dy, Jennifer and Erdogmus, Deniz and Ioannidis, Stratis and Kim, Sang J and others},\n  journal={JAMA ophthalmology},\n  volume={137},\n  number={9},\n  pages={1022--1028},\n  year={2019},\n  publisher={American Medical Association}\n}\n\n
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\n \n\n \n \n \n \n \n A quantitative severity scale for retinopathy of prematurity using deep learning to monitor disease regression after treatment.\n \n \n \n\n\n \n Gupta, K.; Campbell, J P.; Taylor, S.; Brown, J. M; Ostmo, S.; Chan, R. P.; Dy, J.; Erdogmus, D.; Ioannidis, S.; Kalpathy-Cramer, J.; and others\n\n\n \n\n\n\n JAMA ophthalmology, 137(9): 1029–1036. 2019.\n \n\n\n\n
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@article{gupta2019quantitative,\n  title={A quantitative severity scale for retinopathy of prematurity using deep learning to monitor disease regression after treatment},\n  author={Gupta, Kishan and Campbell, J Peter and Taylor, Stanford and Brown, James M and Ostmo, Susan and Chan, RV Paul and Dy, Jennifer and Erdogmus, Deniz and Ioannidis, Stratis and Kalpathy-Cramer, Jayashree and others},\n  journal={JAMA ophthalmology},\n  volume={137},\n  number={9},\n  pages={1029--1036},\n  year={2019},\n  publisher={American Medical Association}\n}\n\n
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\n \n\n \n \n \n \n \n Resources and datasets for radiomics.\n \n \n \n\n\n \n Chang, K.; Beers, A.; Brown, J.; and Kalpathy-Cramer, J.\n\n\n \n\n\n\n In Radiomics and Radiogenomics, pages 179–189. Chapman and Hall/CRC, 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@incollection{chang2019resources,\n  title={Resources and datasets for radiomics},\n  author={Chang, Ken and Beers, Andrew and Brown, James and Kalpathy-Cramer, Jayashree},\n  booktitle={Radiomics and Radiogenomics},\n  pages={179--189},\n  year={2019},\n  publisher={Chapman and Hall/CRC}\n}\n\n
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\n \n\n \n \n \n \n \n Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with Rupture.\n \n \n \n\n\n \n Silva, M. A; Patel, J.; Kavouridis, V.; Gallerani, T.; Beers, A.; Chang, K.; Hoebel, K. V; Brown, J.; See, A. P; Gormley, W. B; and others\n\n\n \n\n\n\n World neurosurgery, 131: e46–e51. 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{silva2019machine,\n  title={Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with Rupture},\n  author={Silva, Michael A and Patel, Jay and Kavouridis, Vasileios and Gallerani, Troy and Beers, Andrew and Chang, Ken and Hoebel, Katharina V and Brown, James and See, Alfred P and Gormley, William B and others},\n  journal={World neurosurgery},\n  volume={131},\n  pages={e46--e51},\n  year={2019},\n  publisher={Elsevier}\n}\n\n
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\n \n\n \n \n \n \n \n Deep Learning Vessel Segmentation for Microsurgical Free Tissue Transfer.\n \n \n \n\n\n \n Hoebel, K.; Kollar, B.; Chang, K.; Beers, A.; Brown, J.; Patel, J.; Pomahac, B.; and Kalpathy-Cramer, J.\n\n\n \n\n\n\n In APS March Meeting Abstracts, volume 2019, pages L30–007, 2019. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{hoebel2019deep,\n  title={Deep Learning Vessel Segmentation for Microsurgical Free Tissue Transfer},\n  author={Hoebel, Katharina and Kollar, Branislav and Chang, Ken and Beers, Andrew and Brown, James and Patel, Jay and Pomahac, Bohdan and Kalpathy-Cramer, Jayashree},\n  booktitle={APS March Meeting Abstracts},\n  volume={2019},\n  pages={L30--007},\n  year={2019}\n}\n\n
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\n \n\n \n \n \n \n \n A Proposed 1 to 9 Severity Scale for Vascular Abnormalities in Retinopathy of Prematurity.\n \n \n \n\n\n \n Kim, S. J.; Campbell, J P.; Brown, J. M.; Ostmo, S.; Chan, R. V. P.; Kalpathy-Cramer, J.; and Chiang, M. F\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 60(9): 4757–4757. 2019.\n \n\n\n\n
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@article{kim2019proposed,\n  title={A Proposed 1 to 9 Severity Scale for Vascular Abnormalities in Retinopathy of Prematurity},\n  author={Kim, Sang Jin and Campbell, J Peter and Brown, James Martin and Ostmo, Susan and Chan, Robison Vernon Paul and Kalpathy-Cramer, Jayashree and Chiang, Michael F},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={60},\n  number={9},\n  pages={4757--4757},\n  year={2019},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Analysis of the Imaging and Informatics Retinopathy of Prematurity (i-ROP) Vascular Severity Score in Patients with Treatment Requiring Retinopathy of Prematurity.\n \n \n \n\n\n \n Choi, R.; Brown, J. M.; Kalpathy-Cramer, J.; Chan, R. P.; Ostmo, S.; Campbell, J P.; and Chiang, M. F\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 60(9): 4758–4758. 2019.\n \n\n\n\n
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@article{choi2019analysis,\n  title={Analysis of the Imaging and Informatics Retinopathy of Prematurity (i-ROP) Vascular Severity Score in Patients with Treatment Requiring Retinopathy of Prematurity},\n  author={Choi, Rene and Brown, James Martin and Kalpathy-Cramer, Jayashree and Chan, RV Paul and Ostmo, Susan and Campbell, J Peter and Chiang, Michael F},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={60},\n  number={9},\n  pages={4758--4758},\n  year={2019},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Utilization of a Deep Learning Image Assessment Tool for Epidemiologic Surveillance of Retinopathy of Prematurity.\n \n \n \n\n\n \n Redd, T.; Campbell, J P.; Brown, J. M.; Shah, P.; Kim, S. J.; Ostmo, S.; Chan, R. V. P.; Dy, J.; Erdogmus, D.; Ioannidis, S.; and others\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 60(9): 1523–1523. 2019.\n \n\n\n\n
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@article{redd2019utilization,\n  title={Utilization of a Deep Learning Image Assessment Tool for Epidemiologic Surveillance of Retinopathy of Prematurity},\n  author={Redd, Travis and Campbell, J Peter and Brown, James Martin and Shah, Parag and Kim, Sang Jin and Ostmo, Susan and Chan, Robison Vernon Paul and Dy, Jennifer and Erdogmus, Deniz and Ioannidis, Stratis and others},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={60},\n  number={9},\n  pages={1523--1523},\n  year={2019},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Deep learning for automated diagnosis of plus disease in Indian ROP patients.\n \n \n \n\n\n \n Kalpathy-Cramer, J.; Brown, J. M.; Coyner, A. S; Hu, S.; Shahrawat, M.; Ostmo, S.; Campbell, J P.; Chan, R. V. P.; Shah, P.; and Chiang, M. F\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 60(9): 1524–1524. 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{kalpathy2019deep,\n  title={Deep learning for automated diagnosis of plus disease in Indian ROP patients},\n  author={Kalpathy-Cramer, Jayashree and Brown, James Martin and Coyner, Aaron S and Hu, Szu-Yeu and Shahrawat, Malika and Ostmo, Susan and Campbell, J Peter and Chan, Robison Vernon Paul and Shah, Parag and Chiang, Michael F},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={60},\n  number={9},\n  pages={1524--1524},\n  year={2019},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Deep learning for monitoring rop progression.\n \n \n \n\n\n \n Gupta, K.; Taylor, S.; Campbell, J P.; Kalpathy-Cramer, J.; Brown, J. M; Chan, R. P.; Kim, S. J; and Chiang, M. F\n\n\n \n\n\n\n Journal of American Association for Pediatric Ophthalmology and Strabismus, 23(4): e8–e9. 2019.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{gupta2019deep,\n  title={Deep learning for monitoring rop progression},\n  author={Gupta, Kishan and Taylor, Stanford and Campbell, J Peter and Kalpathy-Cramer, Jayashree and Brown, James M and Chan, RV Paul and Kim, Sang J and Chiang, Michael F},\n  journal={Journal of American Association for Pediatric Ophthalmology and Strabismus},\n  volume={23},\n  number={4},\n  pages={e8--e9},\n  year={2019},\n  publisher={Mosby}\n}\n\n
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\n \n\n \n \n \n \n \n Use of a Deep Learning-Based Disease Severity Scale for Assessment of Retinopathy of Prematurity Primary Prevention in India.\n \n \n \n\n\n \n Redd, T. K; Brown, J. M; Shah, P. K; Rajan, R.; Ostmo, S.; Chan, R.; Venkatapathy, N.; Hu, S.; Singh, P.; Chiang, M. F; and others\n\n\n \n\n\n\n Narendran and Hu, Szu-Yeu and Singh, Praveer and Chiang, Michael F. and Kalpathy-Cramer, Jayashree and Campbell, John, Use of a Deep Learning-Based Disease Severity Scale for Assessment of Retinopathy of Prematurity Primary Prevention in India (March 11, 2019). 2019.\n \n\n\n\n
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@article{redd2019use,\n  title={Use of a Deep Learning-Based Disease Severity Scale for Assessment of Retinopathy of Prematurity Primary Prevention in India},\n  author={Redd, Travis K and Brown, James M and Shah, Parag K and Rajan, Renu and Ostmo, Susan and Chan, RV and Venkatapathy, Narendran and Hu, Szu-Yeu and Singh, Praveer and Chiang, Michael F and others},\n  journal={Narendran and Hu, Szu-Yeu and Singh, Praveer and Chiang, Michael F. and Kalpathy-Cramer, Jayashree and Campbell, John, Use of a Deep Learning-Based Disease Severity Scale for Assessment of Retinopathy of Prematurity Primary Prevention in India (March 11, 2019)},\n  year={2019}\n}\n\n
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\n \n\n \n \n \n \n \n CareNets: Efficient homomorphic CNN for high resolution images.\n \n \n \n\n\n \n Jin, C.; Al Badawi, A.; Unnikrishnan, J. B.; Mun, C. F.; Brown, J. M; Campbell, J P.; Chiang, M.; Kalpathy-Cramer, J.; Chandrasekhar, V. R.; Krishnaswamy, P.; and others\n\n\n \n\n\n\n In NeurIPS Workshop on Privacy in Machine Learning (PriML), 2019. \n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{jin2019carenets,\n  title={CareNets: Efficient homomorphic CNN for high resolution images},\n  author={Jin, Chao and Al Badawi, Ahmad and Unnikrishnan, JL Balagopal and Mun, Chan Fook and Brown, James M and Campbell, J Peter and Chiang, Michael and Kalpathy-Cramer, Jayashree and Chandrasekhar, Vijay Ramaseshan and Krishnaswamy, Pavitra and others},\n  booktitle={NeurIPS Workshop on Privacy in Machine Learning (PriML)},\n  year={2019}\n}\n\n
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\n \n\n \n \n \n \n \n Analysis of dimensionality reduction techniques in a deep convolutional neural network for the diagnosis of plus disease in retinopathy of prematurity.\n \n \n \n\n\n \n Campbell, J P.; Brown, J. M.; Kalpathy-Cramer, J.; Chan, R. P.; and Chiang, M. F\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 60(9): 1522–1522. 2019.\n \n\n\n\n
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@article{campbell2019analysis,\n  title={Analysis of dimensionality reduction techniques in a deep convolutional neural network for the diagnosis of plus disease in retinopathy of prematurity},\n  author={Campbell, J Peter and Brown, James Martin and Kalpathy-Cramer, Jayashree and Chan, RV Paul and Chiang, Michael F},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={60},\n  number={9},\n  pages={1522--1522},\n  year={2019},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Quantitative analysis of aggressive posterior retinopathy of prematurity using deep learning.\n \n \n \n\n\n \n Smith, K. N; Kim, S. J.; Goldstein, I.; Ostmo, S.; Chan, R. P.; Brown, J. M.; Kalpathy-Cramer, J.; Campbell, J P.; and Chiang, M. F\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 60(9): 4759–4759. 2019.\n \n\n\n\n
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@article{smith2019quantitative,\n  title={Quantitative analysis of aggressive posterior retinopathy of prematurity using deep learning},\n  author={Smith, Kellyn N and Kim, Sang Jin and Goldstein, Isaac and Ostmo, Susan and Chan, RV Paul and Brown, James Martin and Kalpathy-Cramer, Jayashree and Campbell, J Peter and Chiang, Michael F},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={60},\n  number={9},\n  pages={4759--4759},\n  year={2019},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Telemedicine for ROP Diagnosis in a Real-World System: Feasibility of Implementing Artificial Intelligence for Disease Screening.\n \n \n \n\n\n \n Greenwald, M. F; Danford, I.; Shahrawat, M.; Ostmo, S.; Brown, J. M.; Kalpathy-Cramer, J.; Schelonka, R.; Cohen, H. S; Campbell, J P.; and Chiang, M. F\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 60(9): 1526–1526. 2019.\n \n\n\n\n
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@article{greenwald2019telemedicine,\n  title={Telemedicine for ROP Diagnosis in a Real-World System: Feasibility of Implementing Artificial Intelligence for Disease Screening},\n  author={Greenwald, Miles F and Danford, Ian and Shahrawat, Malika and Ostmo, Susan and Brown, James Martin and Kalpathy-Cramer, Jayashree and Schelonka, Robert and Cohen, Howard S and Campbell, J Peter and Chiang, Michael F},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={60},\n  number={9},\n  pages={1526--1526},\n  year={2019},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n  \n 2018\n \n \n (29)\n \n \n
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\n \n\n \n \n \n \n \n Partition and inclusion hierarchies of images: A comprehensive survey.\n \n \n \n\n\n \n Bosilj, P.; Kijak, E.; and Lefèvre, S.\n\n\n \n\n\n\n Journal of Imaging, 4(2): 33. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{bosilj2018partition,\n  title={Partition and inclusion hierarchies of images: A comprehensive survey},\n  author={Bosilj, Petra and Kijak, Ewa and Lef{\\`e}vre, S{\\'e}bastien},\n  journal={Journal of Imaging},\n  volume={4},\n  number={2},\n  pages={33},\n  year={2018},\n  publisher={MDPI}\n}\n\n
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\n \n\n \n \n \n \n \n Connected attribute morphology for unified vegetation segmentation and classification in precision agriculture.\n \n \n \n\n\n \n Bosilj, P.; Duckett, T.; and Cielniak, G.\n\n\n \n\n\n\n Computers in industry, 98: 226–240. 2018.\n \n\n\n\n
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@article{bosilj2018connected,\n  title={Connected attribute morphology for unified vegetation segmentation and classification in precision agriculture},\n  author={Bosilj, Petra and Duckett, Tom and Cielniak, Grzegorz},\n  journal={Computers in industry},\n  volume={98},\n  pages={226--240},\n  year={2018},\n  publisher={Elsevier}\n}\n\n
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\n \n\n \n \n \n \n \n Analysis of morphology-based features for classification of crop and weeds in precision agriculture.\n \n \n \n\n\n \n Bosilj, P.; Duckett, T.; and Cielniak, G.\n\n\n \n\n\n\n IEEE Robotics and Automation Letters, 3(4): 2950–2956. 2018.\n \n\n\n\n
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@article{bosilj2018analysis,\n  title={Analysis of morphology-based features for classification of crop and weeds in precision agriculture},\n  author={Bosilj, Petra and Duckett, Tom and Cielniak, Grzegorz},\n  journal={IEEE Robotics and Automation Letters},\n  volume={3},\n  number={4},\n  pages={2950--2956},\n  year={2018},\n  publisher={IEEE}\n}\n\n
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\n \n\n \n \n \n \n \n A novel camera based approach for automatic expiry date detection and recognition on food packages.\n \n \n \n\n\n \n Gong, L.; Yu, M.; Duan, W.; Ye, X.; Gudmundsson, K.; and Swainson, M.\n\n\n \n\n\n\n In Artificial Intelligence Applications and Innovations: 14th IFIP WG 12.5 International Conference, AIAI 2018, Rhodes, Greece, May 25–27, 2018, Proceedings 14, pages 133–142, 2018. Springer International Publishing\n \n\n\n\n
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@inproceedings{gong2018novel,\n  title={A novel camera based approach for automatic expiry date detection and recognition on food packages},\n  author={Gong, Liyun and Yu, Miao and Duan, Wenting and Ye, Xujiong and Gudmundsson, Kjartan and Swainson, Mark},\n  booktitle={Artificial Intelligence Applications and Innovations: 14th IFIP WG 12.5 International Conference, AIAI 2018, Rhodes, Greece, May 25--27, 2018, Proceedings 14},\n  pages={133--142},\n  year={2018},\n  organization={Springer International Publishing}\n}\n\n
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\n \n\n \n \n \n \n \n Classification of bird species from video using appearance and motion features.\n \n \n \n\n\n \n Atanbori, J.; Duan, W.; Shaw, E.; Appiah, K.; and Dickinson, P.\n\n\n \n\n\n\n Ecological Informatics, 48: 12–23. 2018.\n \n\n\n\n
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@article{atanbori2018classification,\n  title={Classification of bird species from video using appearance and motion features},\n  author={Atanbori, John and Duan, Wenting and Shaw, Edward and Appiah, Kofi and Dickinson, Patrick},\n  journal={Ecological Informatics},\n  volume={48},\n  pages={12--23},\n  year={2018},\n  publisher={Elsevier}\n}\n\n
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\n \n\n \n \n \n \n \n Sequential neural networks for biologically informed glioma segmentation.\n \n \n \n\n\n \n Beers, A.; Chang, K.; Brown, J.; Gerstner, E.; Rosen, B.; and Kalpathy-Cramer, J.\n\n\n \n\n\n\n In Medical Imaging 2018: Image Processing, volume 10574, pages 807–816, 2018. SPIE\n \n\n\n\n
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@inproceedings{beers2018sequential,\n  title={Sequential neural networks for biologically informed glioma segmentation},\n  author={Beers, Andrew and Chang, Ken and Brown, James and Gerstner, Elizabeth and Rosen, Bruce and Kalpathy-Cramer, Jayashree},\n  booktitle={Medical Imaging 2018: Image Processing},\n  volume={10574},\n  pages={807--816},\n  year={2018},\n  organization={SPIE}\n}\n\n
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\n \n\n \n \n \n \n \n Fully automated disease severity assessment and treatment monitoring in retinopathy of prematurity using deep learning.\n \n \n \n\n\n \n Brown, J. M; Campbell, J P.; Beers, A.; Chang, K.; Donohue, K.; Ostmo, S.; Chan, R. P.; Dy, J.; Erdogmus, D.; Ioannidis, S.; and others\n\n\n \n\n\n\n In Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications, volume 10579, pages 149–155, 2018. SPIE\n \n\n\n\n
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@inproceedings{brown2018fully,\n  title={Fully automated disease severity assessment and treatment monitoring in retinopathy of prematurity using deep learning},\n  author={Brown, James M and Campbell, J Peter and Beers, Andrew and Chang, Ken and Donohue, Kyra and Ostmo, Susan and Chan, RV Paul and Dy, Jennifer and Erdogmus, Deniz and Ioannidis, Stratis and others},\n  booktitle={Medical Imaging 2018: Imaging Informatics for Healthcare, Research, and Applications},\n  volume={10579},\n  pages={149--155},\n  year={2018},\n  organization={SPIE}\n}\n\n
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\n \n\n \n \n \n \n \n Automated diagnosis of plus disease in retinopathy of prematurity using deep convolutional neural networks.\n \n \n \n\n\n \n Brown, J. M; Campbell, J P.; Beers, A.; Chang, K.; Ostmo, S.; Chan, R. P.; Dy, J.; Erdogmus, D.; Ioannidis, S.; Kalpathy-Cramer, J.; and others\n\n\n \n\n\n\n JAMA ophthalmology, 136(7): 803–810. 2018.\n \n\n\n\n
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@article{brown2018automated,\n  title={Automated diagnosis of plus disease in retinopathy of prematurity using deep convolutional neural networks},\n  author={Brown, James M and Campbell, J Peter and Beers, Andrew and Chang, Ken and Ostmo, Susan and Chan, RV Paul and Dy, Jennifer and Erdogmus, Deniz and Ioannidis, Stratis and Kalpathy-Cramer, Jayashree and others},\n  journal={JAMA ophthalmology},\n  volume={136},\n  number={7},\n  pages={803--810},\n  year={2018},\n  publisher={American Medical Association}\n}\n\n
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\n \n\n \n \n \n \n \n ISLES 2016 and 2017-benchmarking ischemic stroke lesion outcome prediction based on multispectral MRI.\n \n \n \n\n\n \n Winzeck, S.; Hakim, A.; McKinley, R.; Pinto, J. A.; Alves, V.; Silva, C.; Pisov, M.; Krivov, E.; Belyaev, M.; Monteiro, M.; and others\n\n\n \n\n\n\n Frontiers in neurology,679. 2018.\n \n\n\n\n
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@article{winzeck2018isles,\n  title={ISLES 2016 and 2017-benchmarking ischemic stroke lesion outcome prediction based on multispectral MRI},\n  author={Winzeck, Stefan and Hakim, Arsany and McKinley, Richard and Pinto, Jos{\\'e} AADSR and Alves, Victor and Silva, Carlos and Pisov, Maxim and Krivov, Egor and Belyaev, Mikhail and Monteiro, Miguel and others},\n  journal={Frontiers in neurology},\n  pages={679},\n  year={2018},\n  publisher={Frontiers}\n}\n\n
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\n \n\n \n \n \n \n \n Automated diagnosis of plus disease in retinopathy of prematurity using deep learning.\n \n \n \n\n\n \n Campbell, J P.; Brown, J.; Chan, R. P.; Dy, J.; Ioannidis, S.; Erdogmus, D.; Kalpathy-Cramer, J.; and Chiang, M. F\n\n\n \n\n\n\n Journal of American Association for Pediatric Ophthalmology and Strabismus $\\{$JAAPOS$\\}$, 22(4): e12. 2018.\n \n\n\n\n
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@article{campbell2018automated,\n  title={Automated diagnosis of plus disease in retinopathy of prematurity using deep learning},\n  author={Campbell, J Peter and Brown, James and Chan, RV Paul and Dy, Jennifer and Ioannidis, Stratis and Erdogmus, Deniz and Kalpathy-Cramer, Jayashree and Chiang, Michael F},\n  journal={Journal of American Association for Pediatric Ophthalmology and Strabismus $\\{$JAAPOS$\\}$},\n  volume={22},\n  number={4},\n  pages={e12},\n  year={2018},\n  publisher={Elsevier}\n}\n\n
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\n \n\n \n \n \n \n \n How is plus disease diagnosed in ROP? Insights from a deep learning computer-based image analysis system with occlusion analysis.\n \n \n \n\n\n \n Ghergherehchi, L. M; Brown, J. M; Ostmo, S.; Kim, S. J.; Campbell, J. P; Chan, R. P.; Kalpathy-Cramer, J.; and Chiang, M. F\n\n\n \n\n\n\n Journal of American Association for Pediatric Ophthalmology and Strabismus $\\{$JAAPOS$\\}$, 22(4): e78. 2018.\n \n\n\n\n
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@article{ghergherehchi2018plus,\n  title={How is plus disease diagnosed in ROP? Insights from a deep learning computer-based image analysis system with occlusion analysis},\n  author={Ghergherehchi, Layla M and Brown, James M and Ostmo, Susan and Kim, Sang Jin and Campbell, John P and Chan, RV Paul and Kalpathy-Cramer, Jayashree and Chiang, Michael F},\n  journal={Journal of American Association for Pediatric Ophthalmology and Strabismus $\\{$JAAPOS$\\}$},\n  volume={22},\n  number={4},\n  pages={e78},\n  year={2018},\n  publisher={Elsevier}\n}\n\n
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\n \n\n \n \n \n \n \n Application of a Quantitative Image Analysis Scale Using Deep Learning for Detection of Clinically Significant ROP.\n \n \n \n\n\n \n Redd, T.; Campbell, J P.; Brown, J. M; Kim, S. J.; Ostmo, S.; Chan, R. V. P.; Dy, J.; Erdogmus, D.; Ioannidis, S.; Kalpathy-Cramer, J.; and others\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 59(9): 2782–2782. 2018.\n \n\n\n\n
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@article{redd2018application,\n  title={Application of a Quantitative Image Analysis Scale Using Deep Learning for Detection of Clinically Significant ROP},\n  author={Redd, Travis and Campbell, J Peter and Brown, James M and Kim, Sang Jin and Ostmo, Susan and Chan, Robison Vernon Paul and Dy, Jennifer and Erdogmus, Deniz and Ioannidis, Stratis and Kalpathy-Cramer, Jayashree and others},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={59},\n  number={9},\n  pages={2782--2782},\n  year={2018},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Artificial intelligence in retinopathy of prematurity: development of a fully automated deep convolutional neural network (DeepROP) for plus disease diagnosis.\n \n \n \n\n\n \n Brown, J. M; Campbell, J P.; Ostmo, S.; Tian, P.; Yildiz, V.; Kim, S. J.; Chan, R. V. P.; Dy, J.; Erdogmus, D.; Ioannidis, S.; and others\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 59(9): 3938–3938. 2018.\n \n\n\n\n
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@article{brown2018artificial,\n  title={Artificial intelligence in retinopathy of prematurity: development of a fully automated deep convolutional neural network (DeepROP) for plus disease diagnosis},\n  author={Brown, James M and Campbell, J Peter and Ostmo, Susan and Tian, Peng and Yildiz, Veysi and Kim, Sang Jin and Chan, Robison Vernon Paul and Dy, Jennifer and Erdogmus, Deniz and Ioannidis, Stratis and others},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={59},\n  number={9},\n  pages={3938--3938},\n  year={2018},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Automated Computer-Based Image Analysis in Monitoring Disease Progression for Retinopathy of Prematurity.\n \n \n \n\n\n \n Taylor, S.; Gupta, K.; Campbell, J P.; Brown, J. M; Ostmo, S.; Chan, R. V. P.; Dy, J.; Ioannidis, S.; Kalpathy-Cramer, J.; Kim, S. J.; and others\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 59(9): 3937–3937. 2018.\n \n\n\n\n
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@article{taylor2018automated,\n  title={Automated Computer-Based Image Analysis in Monitoring Disease Progression for Retinopathy of Prematurity},\n  author={Taylor, Stanford and Gupta, Kishan and Campbell, J Peter and Brown, James M and Ostmo, Susan and Chan, Robison Vernon Paul and Dy, Jennifer and Ioannidis, Stratis and Kalpathy-Cramer, Jayashree and Kim, Sang Jin and others},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={59},\n  number={9},\n  pages={3937--3937},\n  year={2018},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Artificial intelligence in retinopathy of prematurity: identification of clinically significant retinal vascular findings using computer-based image analysis.\n \n \n \n\n\n \n Chiang, M. F; Brown, J. M; Yildiz, V.; Tian, P.; Ghergherehchi, L.; Campbell, J P.; Ostmo, S.; Kim, S. J.; Chan, R. V. P.; Dy, J.; and others\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 59(9): 2764–2764. 2018.\n \n\n\n\n
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@article{chiang2018artificial,\n  title={Artificial intelligence in retinopathy of prematurity: identification of clinically significant retinal vascular findings using computer-based image analysis},\n  author={Chiang, Michael F and Brown, James M and Yildiz, Veysi and Tian, Peng and Ghergherehchi, Layla and Campbell, J Peter and Ostmo, Susan and Kim, Sang Jin and Chan, Robison Vernon Paul and Dy, Jennifer and others},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={59},\n  number={9},\n  pages={2764--2764},\n  year={2018},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Artificial intelligence in retinopathy of prematurity (ROP): diagnostic performance of a supervised machine learning system (i-ROP ASSIST).\n \n \n \n\n\n \n Ostmo, S.; Yildiz, V.; Tian, P.; Brown, J. M; Campbell, J P.; Kim, S. J.; Dy, J.; Ioannidis, S.; Erdogmus, D.; Chan, R. V. P.; and others\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 59(9): 2772–2772. 2018.\n \n\n\n\n
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@article{ostmo2018artificial,\n  title={Artificial intelligence in retinopathy of prematurity (ROP): diagnostic performance of a supervised machine learning system (i-ROP ASSIST)},\n  author={Ostmo, Susan and Yildiz, Veysi and Tian, Peng and Brown, James M and Campbell, J Peter and Kim, Sang Jin and Dy, Jennifer and Ioannidis, Stratis and Erdogmus, Deniz and Chan, Robison Vernon Paul and others},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={59},\n  number={9},\n  pages={2772--2772},\n  year={2018},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Monitoring response to treatment in severe retinopathy of prematurity using a deep learning based quantitative severity scale.\n \n \n \n\n\n \n Gupta, K.; Campbell, J P.; Taylor, S.; Brown, J. M; Ostmo, S.; Chan, R. P.; Dy, J.; Erdogmus, D.; Ioannidis, S.; Kalpathy-Cramer, J.; and others\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 59(9): 3766–3766. 2018.\n \n\n\n\n
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@article{gupta2018monitoring,\n  title={Monitoring response to treatment in severe retinopathy of prematurity using a deep learning based quantitative severity scale},\n  author={Gupta, Kishan and Campbell, J Peter and Taylor, Stanford and Brown, James M and Ostmo, Susan and Chan, RV Paul and Dy, Jennifer and Erdogmus, Deniz and Ioannidis, Stratis and Kalpathy-Cramer, Jayashree and others},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={59},\n  number={9},\n  pages={3766--3766},\n  year={2018},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Risk assessment in retinopathy of prematurity: improvement of clinical models using automated image analysis.\n \n \n \n\n\n \n Kalpathy-Cramer, J.; Brown, J. M; Campbell, J P.; Ostmo, S.; Tian, P.; Yildiz, V.; Kim, S. J.; Chan, R. V. P.; Dy, J.; Erdogmus, D.; and others\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 59(9): 2767–2767. 2018.\n \n\n\n\n
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@article{kalpathy2018risk,\n  title={Risk assessment in retinopathy of prematurity: improvement of clinical models using automated image analysis},\n  author={Kalpathy-Cramer, Jayashree and Brown, James M and Campbell, J Peter and Ostmo, Susan and Tian, Peng and Yildiz, Veysi and Kim, Sang Jin and Chan, Robison Vernon Paul and Dy, Jennifer and Erdogmus, Deniz and others},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={59},\n  number={9},\n  pages={2767--2767},\n  year={2018},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Deep learning for image quality assessment of fundus images in retinopathy of prematurity.\n \n \n \n\n\n \n Coyner, A. S; Swan, R.; Brown, J. M; Kalpathy-Cramer, J.; Kim, S. J.; Campbell, J P.; Jonas, K.; Chan, R. P.; Ostmo, S.; and Chiang, M. F\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 59(9): 2762–2762. 2018.\n \n\n\n\n
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@article{coyner2018deep,\n  title={Deep learning for image quality assessment of fundus images in retinopathy of prematurity},\n  author={Coyner, Aaron S and Swan, Ryan and Brown, James M and Kalpathy-Cramer, Jayashree and Kim, Sang Jin and Campbell, J Peter and Jonas, Karyn and Chan, RV Paul and Ostmo, Susan and Chiang, Michael F},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={59},\n  number={9},\n  pages={2762--2762},\n  year={2018},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Distributed deep learning networks among institutions for medical imaging.\n \n \n \n\n\n \n Chang, K.; Balachandar, N.; Lam, C.; Yi, D.; Brown, J.; Beers, A.; Rosen, B.; Rubin, D. L; and Kalpathy-Cramer, J.\n\n\n \n\n\n\n Journal of the American Medical Informatics Association, 25(8): 945–954. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{chang2018distributed,\n  title={Distributed deep learning networks among institutions for medical imaging},\n  author={Chang, Ken and Balachandar, Niranjan and Lam, Carson and Yi, Darvin and Brown, James and Beers, Andrew and Rosen, Bruce and Rubin, Daniel L and Kalpathy-Cramer, Jayashree},\n  journal={Journal of the American Medical Informatics Association},\n  volume={25},\n  number={8},\n  pages={945--954},\n  year={2018},\n  publisher={Oxford University Press}\n}\n\n
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\n \n\n \n \n \n \n \n Deep feature transfer between localization and segmentation tasks.\n \n \n \n\n\n \n Hu, S.; Beers, A.; Chang, K.; Höbel, K.; Campbell, J P.; Erdogumus, D.; Ioannidis, S.; Dy, J.; Chiang, M. F; Kalpathy-Cramer, J.; and others\n\n\n \n\n\n\n arXiv preprint arXiv:1811.02539. 2018.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{hu2018deep,\n  title={Deep feature transfer between localization and segmentation tasks},\n  author={Hu, Szu-Yeu and Beers, Andrew and Chang, Ken and H{\\"o}bel, Kathi and Campbell, J Peter and Erdogumus, Deniz and Ioannidis, Stratis and Dy, Jennifer and Chiang, Michael F and Kalpathy-Cramer, Jayashree and others},\n  journal={arXiv preprint arXiv:1811.02539},\n  year={2018}\n}\n\n
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\n \n\n \n \n \n \n \n NIMG-63. ADVANCED IMAGING FOR ASSESSING VOLUMETRIC RESPONSES IN BRAIN METASTASES TREATED WITH CHECKPOINT BLOCKADE.\n \n \n \n\n\n \n Gerstner, E.; Cardona, J.; Chang, K.; Beers, A.; Brown, J.; Kalpathy-Cramer, J.; Lee, E.; Lin, N.; Tolaney, S.; Nayak, L.; and others\n\n\n \n\n\n\n Neuro-Oncology, 20(suppl_6): vi190–vi190. 2018.\n \n\n\n\n
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@article{gerstner2018nimg,\n  title={NIMG-63. ADVANCED IMAGING FOR ASSESSING VOLUMETRIC RESPONSES IN BRAIN METASTASES TREATED WITH CHECKPOINT BLOCKADE},\n  author={Gerstner, Elizabeth and Cardona, Jonathan and Chang, Ken and Beers, Andrew and Brown, James and Kalpathy-Cramer, Jayashree and Lee, Eudocia and Lin, Nancy and Tolaney, Sara and Nayak, Lakshmi and others},\n  journal={Neuro-Oncology},\n  volume={20},\n  number={suppl\\_6},\n  pages={vi190--vi190},\n  year={2018},\n  publisher={Oxford University Press US}\n}\n\n
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\n \n\n \n \n \n \n \n NCOG-04. EFFECTS OF PROTON RADIATION ON BRAIN STRUCTURE AND FUNCTION IN LOW GRADE GLIOMA.\n \n \n \n\n\n \n Parsons, M.; Hoebel, K.; Chang, K.; Pongpitakmetha, T.; Beers, A.; Brown, J.; Kalpathy-Cramer, J.; Sherman, J.; Shih, H.; and Dietrich, J.\n\n\n \n\n\n\n Neuro-Oncology, 20(suppl_6): vi173–vi173. 2018.\n \n\n\n\n
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@article{parsons2018ncog,\n  title={NCOG-04. EFFECTS OF PROTON RADIATION ON BRAIN STRUCTURE AND FUNCTION IN LOW GRADE GLIOMA},\n  author={Parsons, Michael and Hoebel, Katharina and Chang, Ken and Pongpitakmetha, Thanakit and Beers, Andrew and Brown, James and Kalpathy-Cramer, Jayashree and Sherman, Janet and Shih, Helen and Dietrich, Jorg},\n  journal={Neuro-Oncology},\n  volume={20},\n  number={suppl\\_6},\n  pages={vi173--vi173},\n  year={2018},\n  publisher={Oxford University Press US}\n}\n\n
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\n \n\n \n \n \n \n \n High-resolution medical image synthesis using progressively grown generative adversarial networks.\n \n \n \n\n\n \n Beers, A.; Brown, J.; Chang, K.; Campbell, J P.; Ostmo, S.; Chiang, M. F; and Kalpathy-Cramer, J.\n\n\n \n\n\n\n arXiv preprint arXiv:1805.03144. 2018.\n \n\n\n\n
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@article{beers2018high,\n  title={High-resolution medical image synthesis using progressively grown generative adversarial networks},\n  author={Beers, Andrew and Brown, James and Chang, Ken and Campbell, J Peter and Ostmo, Susan and Chiang, Michael F and Kalpathy-Cramer, Jayashree},\n  journal={arXiv preprint arXiv:1805.03144},\n  year={2018}\n}\n\n
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\n \n\n \n \n \n \n \n Machine learning for health (ML4H) workshop at NeurIPS 2018.\n \n \n \n\n\n \n Antropova, N.; Beam, A. L; Beaulieu-Jones, B. K; Chen, I.; Chivers, C.; Dalca, A.; Finlayson, S.; Fiterau, M.; Fries, J. A.; Ghassemi, M.; and others\n\n\n \n\n\n\n arXiv preprint arXiv:1811.07216. 2018.\n \n\n\n\n
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@article{antropova2018machine,\n  title={Machine learning for health (ML4H) workshop at NeurIPS 2018},\n  author={Antropova, Natalia and Beam, Andrew L and Beaulieu-Jones, Brett K and Chen, Irene and Chivers, Corey and Dalca, Adrian and Finlayson, Sam and Fiterau, Madalina and Fries, Jason Alan and Ghassemi, Marzyeh and others},\n  journal={arXiv preprint arXiv:1811.07216},\n  year={2018}\n}\n\n
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\n \n\n \n \n \n \n \n Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge.\n \n \n \n\n\n \n Bakas, S.; Reyes, M.; Jakab, A.; Bauer, S.; Rempfler, M.; Crimi, A.; Shinohara, R. T.; Berger, C.; Ha, S. M.; Rozycki, M.; and others\n\n\n \n\n\n\n arXiv preprint arXiv:1811.02629. 2018.\n \n\n\n\n
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@article{bakas2018identifying,\n  title={Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge},\n  author={Bakas, Spyridon and Reyes, Mauricio and Jakab, Andras and Bauer, Stefan and Rempfler, Markus and Crimi, Alessandro and Shinohara, Russell Takeshi and Berger, Christoph and Ha, Sung Min and Rozycki, Martin and others},\n  journal={arXiv preprint arXiv:1811.02629},\n  year={2018}\n}\n\n
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\n \n\n \n \n \n \n \n Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images.\n \n \n \n\n\n \n Lecouat, B.; Chang, K.; Foo, C.; Unnikrishnan, B.; Brown, J. M; Zenati, H.; Beers, A.; Chandrasekhar, V.; Kalpathy-Cramer, J.; and Krishnaswamy, P.\n\n\n \n\n\n\n arXiv preprint arXiv:1812.07832. 2018.\n \n\n\n\n
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@article{lecouat2018semi,\n  title={Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images},\n  author={Lecouat, Bruno and Chang, Ken and Foo, Chuan-Sheng and Unnikrishnan, Balagopal and Brown, James M and Zenati, Houssam and Beers, Andrew and Chandrasekhar, Vijay and Kalpathy-Cramer, Jayashree and Krishnaswamy, Pavitra},\n  journal={arXiv preprint arXiv:1812.07832},\n  year={2018}\n}\n\n
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\n \n\n \n \n \n \n \n Anatomical DCE-MRI phantoms generated from glioma patient data.\n \n \n \n\n\n \n Beers, A.; Chang, K.; Brown, J.; Zhu, X.; Sengupta, D.; Willke, T. L; Gerstner, E.; Rosen, B.; and Kalpathy-Cramer, J.\n\n\n \n\n\n\n In Medical Imaging 2018: Physics of Medical Imaging, volume 10573, pages 743–748, 2018. SPIE\n \n\n\n\n
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@inproceedings{beers2018anatomical,\n  title={Anatomical DCE-MRI phantoms generated from glioma patient data},\n  author={Beers, Andrew and Chang, Ken and Brown, James and Zhu, Xia and Sengupta, Dipanjan and Willke, Theodore L and Gerstner, Elizabeth and Rosen, Bruce and Kalpathy-Cramer, Jayashree},\n  booktitle={Medical Imaging 2018: Physics of Medical Imaging},\n  volume={10573},\n  pages={743--748},\n  year={2018},\n  organization={SPIE}\n}\n\n
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\n \n\n \n \n \n \n \n Artificial intelligence in retinopathy of prematurity: clinical validation of a fully automated deep learning system (i-ROP DL) for plus disease diagnosis.\n \n \n \n\n\n \n Campbell, J P.; Brown, J. M; Ostmo, S.; Chan, R. P.; Dy, J.; Erdogmus, D.; Ioannidis, S.; Kalpathy-Cramer, J.; and Chiang, M. F\n\n\n \n\n\n\n Investigative Ophthalmology & Visual Science, 59(9): 3936–3936. 2018.\n \n\n\n\n
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@article{campbell2018artificial,\n  title={Artificial intelligence in retinopathy of prematurity: clinical validation of a fully automated deep learning system (i-ROP DL) for plus disease diagnosis},\n  author={Campbell, J Peter and Brown, James M and Ostmo, Susan and Chan, RV Paul and Dy, Jennifer and Erdogmus, Deniz and Ioannidis, Stratis and Kalpathy-Cramer, Jayashree and Chiang, Michael F},\n  journal={Investigative Ophthalmology \\& Visual Science},\n  volume={59},\n  number={9},\n  pages={3936--3936},\n  year={2018},\n  publisher={The Association for Research in Vision and Ophthalmology}\n}\n\n
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\n \n\n \n \n \n \n \n Detection and characterisation of bone destruction in murine rheumatoid arthritis using statistical shape models.\n \n \n \n\n\n \n Brown, J. M; Ross, E.; Desanti, G.; Saghir, A.; Clark, A.; Buckley, C.; Filer, A.; Naylor, A.; and Claridge, E.\n\n\n \n\n\n\n Medical image analysis, 40: 30–43. 2017.\n \n\n\n\n
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@article{brown2017detection,\n  title={Detection and characterisation of bone destruction in murine rheumatoid arthritis using statistical shape models},\n  author={Brown, James M and Ross, Ewan and Desanti, Guillaume and Saghir, Atif and Clark, Andy and Buckley, Chris and Filer, Andrew and Naylor, Amy and Claridge, Ela},\n  journal={Medical image analysis},\n  volume={40},\n  pages={30--43},\n  year={2017},\n  publisher={Elsevier}\n}\n\n
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\n \n\n \n \n \n \n \n Disease model discovery from 3,328 gene knockouts by The International Mouse Phenotyping Consortium.\n \n \n \n\n\n \n Meehan, T. F; Conte, N.; West, D. B; Jacobsen, J. O; Mason, J.; Warren, J.; Chen, C.; Tudose, I.; Relac, M.; Matthews, P.; and others\n\n\n \n\n\n\n Nature genetics, 49(8): 1231–1238. 2017.\n \n\n\n\n
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@article{meehan2017disease,\n  title={Disease model discovery from 3,328 gene knockouts by The International Mouse Phenotyping Consortium},\n  author={Meehan, Terrence F and Conte, Nathalie and West, David B and Jacobsen, Julius O and Mason, Jeremy and Warren, Jonathan and Chen, Chao-Kung and Tudose, Ilinca and Relac, Mike and Matthews, Peter and others},\n  journal={Nature genetics},\n  volume={49},\n  number={8},\n  pages={1231--1238},\n  year={2017},\n  publisher={Nature Publishing Group US New York}\n}\n\n
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\n \n\n \n \n \n \n \n Sequential 3D U-Nets for Biologically-Informed Brain Tumor Segmentation.\n \n \n \n\n\n \n Beers, A.; Chang, K.; Brown, J.; Sartor, E.; Mammen, C.; Gerstner, E.; Rosen, B.; and Kalpathy-Cramer, J.\n\n\n \n\n\n\n arXiv preprint arXiv:1709.02967. 2017.\n \n\n\n\n
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@article{beers2017sequential,\n  title={Sequential 3D U-Nets for Biologically-Informed Brain Tumor Segmentation},\n  author={Beers, Andrew and Chang, Ken and Brown, James and Sartor, Emmett and Mammen, CP and Gerstner, Elizabeth and Rosen, Bruce and Kalpathy-Cramer, Jayashree},\n  journal={arXiv preprint arXiv:1709.02967},\n  year={2017}\n}\n\n
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\n \n\n \n \n \n \n \n High Throughput Imaging and Phenotyping of Homozygous Lethal Mouse Lines at MRC Harwell.\n \n \n \n\n\n \n Cleak, J.; Johnson, S.; Szoke-Kovacs, Z.; Horner, N.; Brown, J.; Westerberg, H.; and Teboul, L.\n\n\n \n\n\n\n In GENETICS RESEARCH, volume 99, 2017. CAMBRIDGE UNIV PRESS 32 AVENUE OF THE AMERICAS, NEW YORK, NY 10013-2473 USA\n \n\n\n\n
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@inproceedings{cleak2017high,\n  title={High Throughput Imaging and Phenotyping of Homozygous Lethal Mouse Lines at MRC Harwell},\n  author={Cleak, James and Johnson, Sara and Szoke-Kovacs, Zsombor and Horner, Neil and Brown, James and Westerberg, Henrik and Teboul, Lydia},\n  booktitle={GENETICS RESEARCH},\n  volume={99},\n  year={2017},\n  organization={CAMBRIDGE UNIV PRESS 32 AVENUE OF THE AMERICAS, NEW YORK, NY 10013-2473 USA}\n}\n\n
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\n \n\n \n \n \n \n \n Retrieval of remote sensing images with pattern spectra descriptors.\n \n \n \n\n\n \n Bosilj, P.; Aptoula, E.; Lefèvre, S.; and Kijak, E.\n\n\n \n\n\n\n ISPRS International Journal of Geo-Information, 5(12): 228. 2016.\n \n\n\n\n
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@article{bosilj2016retrieval,\n  title={Retrieval of remote sensing images with pattern spectra descriptors},\n  author={Bosilj, Petra and Aptoula, Erchan and Lef{\\`e}vre, S{\\'e}bastien and Kijak, Ewa},\n  journal={ISPRS International Journal of Geo-Information},\n  volume={5},\n  number={12},\n  pages={228},\n  year={2016},\n  publisher={MDPI}\n}\n\n
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\n \n\n \n \n \n \n \n A supervised texton based approach for automatic segmentation and measurement of the fetal head and femur in 2D ultrasound images.\n \n \n \n\n\n \n Zhang, L.; Ye, X.; Lambrou, T.; Duan, W.; Allinson, N.; and Dudley, N. J\n\n\n \n\n\n\n Physics in Medicine & Biology, 61(3): 1095. 2016.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{zhang2016supervised,\n  title={A supervised texton based approach for automatic segmentation and measurement of the fetal head and femur in 2D ultrasound images},\n  author={Zhang, Lei and Ye, Xujiong and Lambrou, Tryphon and Duan, Wenting and Allinson, Nigel and Dudley, Nicholas J},\n  journal={Physics in Medicine \\& Biology},\n  volume={61},\n  number={3},\n  pages={1095},\n  year={2016},\n  publisher={IOP Publishing}\n}\n\n
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\n \n\n \n \n \n \n \n Automatic classification of flying bird species using computer vision techniques.\n \n \n \n\n\n \n Atanbori, J.; Duan, W.; Murray, J.; Appiah, K.; and Dickinson, P.\n\n\n \n\n\n\n Pattern Recognition Letters, 81: 53–62. 2016.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{atanbori2016automatic,\n  title={Automatic classification of flying bird species using computer vision techniques},\n  author={Atanbori, John and Duan, Wenting and Murray, John and Appiah, Kofi and Dickinson, Patrick},\n  journal={Pattern Recognition Letters},\n  volume={81},\n  pages={53--62},\n  year={2016},\n  publisher={Elsevier}\n}\n\n
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\n \n\n \n \n \n \n \n High-throughput discovery of novel developmental phenotypes.\n \n \n \n\n\n \n Dickinson, M. E; Flenniken, A. M; Ji, X.; Teboul, L.; Wong, M. D; White, J. K; Meehan, T. F; Weninger, W. J; Westerberg, H.; Adissu, H.; and others\n\n\n \n\n\n\n Nature, 537(7621): 508–514. 2016.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{dickinson2016high,\n  title={High-throughput discovery of novel developmental phenotypes},\n  author={Dickinson, Mary E and Flenniken, Ann M and Ji, Xiao and Teboul, Lydia and Wong, Michael D and White, Jacqueline K and Meehan, Terrence F and Weninger, Wolfgang J and Westerberg, Henrik and Adissu, Hibret and others},\n  journal={Nature},\n  volume={537},\n  number={7621},\n  pages={508--514},\n  year={2016},\n  publisher={Nature Publishing Group}\n}\n\n
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\n \n\n \n \n \n \n \n A bioimage informatics platform for high-throughput embryo phenotyping.\n \n \n \n\n\n \n Brown, J. M; Horner, N. R; Lawson, T. N; Fiegel, T.; Greenaway, S.; Morgan, H.; Ring, N.; Santos, L.; Sneddon, D.; Teboul, L.; and others\n\n\n \n\n\n\n Briefings in bioinformatics, 19(1): 41–51. 2016.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{brown2016bioimage,\n  title={A bioimage informatics platform for high-throughput embryo phenotyping},\n  author={Brown, James M and Horner, Neil R and Lawson, Thomas N and Fiegel, Tanja and Greenaway, Simon and Morgan, Hugh and Ring, Natalie and Santos, Luis and Sneddon, Duncan and Teboul, Lydia and others},\n  journal={Briefings in bioinformatics},\n  volume={19},\n  number={1},\n  pages={41--51},\n  year={2016},\n  publisher={Oxford University Press}\n}\n\n
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\n  \n 2015\n \n \n (7)\n \n \n
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\n \n\n \n \n \n \n \n A computer vision approach to classification of birds in flight from video sequences.\n \n \n \n\n\n \n Atanbori, J.; Duan, W.; Murray, J.; Appiah, K.; and Dickinson, P.\n\n\n \n\n\n\n . 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{atanbori2015computer,\n  title={A computer vision approach to classification of birds in flight from video sequences},\n  author={Atanbori, John and Duan, Wenting and Murray, John and Appiah, Kofi and Dickinson, Patrick},\n  year={2015},\n  publisher={BMVA Press}\n}\n\n
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\n \n\n \n \n \n \n \n A computer vision approach to classification of birds in flight from video sequences.\n \n \n \n\n\n \n Appiah, K.; Atanbori, J.; Dickinson, P.; Duan, W.; and Murray, J.\n\n\n \n\n\n\n . 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{appiah2015computer,\n  title={A computer vision approach to classification of birds in flight from video sequences},\n  author={Appiah, Kofi and Atanbori, John and Dickinson, Patrick and Duan, Wenting and Murray, John},\n  year={2015},\n  publisher={University of Lincoln}\n}\n\n
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\n \n\n \n \n \n \n \n Articulated statistical shape models for the analysis of bone destruction in mouse models of rheumatoid arthritis.\n \n \n \n\n\n \n Brown, J.\n\n\n \n\n\n\n Ph.D. Thesis, University of Birmingham, 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@phdthesis{brown2015articulated,\n  title={Articulated statistical shape models for the analysis of bone destruction in mouse models of rheumatoid arthritis},\n  author={Brown, James},\n  year={2015},\n  school={University of Birmingham}\n}\n\n
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\n \n\n \n \n \n \n \n Comparative visualization of genotype-phenotype relationships.\n \n \n \n\n\n \n Yaikhom, G.; Morgan, H.; Sneddon, D.; Retha, A.; Atienza-Herrero, J.; Blake, A.; Brown, J.; Di Fenza, A.; Fiegel, T.; Horner, N.; and others\n\n\n \n\n\n\n Nature methods, 12(8): 698–699. 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{yaikhom2015comparative,\n  title={Comparative visualization of genotype-phenotype relationships},\n  author={Yaikhom, Gagarine and Morgan, Hugh and Sneddon, Duncan and Retha, Ahmad and Atienza-Herrero, Julian and Blake, Andrew and Brown, James and Di Fenza, Armida and Fiegel, Tanja and Horner, Neil and others},\n  journal={Nature methods},\n  volume={12},\n  number={8},\n  pages={698--699},\n  year={2015},\n  publisher={Nature Publishing Group}\n}\n\n
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\n \n\n \n \n \n \n \n A mouse informatics platform for phenotypic and translational discovery.\n \n \n \n\n\n \n Ring, N.; Meehan, T. F; Blake, A.; Brown, J.; Chen, C.; Conte, N.; Di Fenza, A.; Fiegel, T.; Horner, N.; Jacobsen, J. O.; and others\n\n\n \n\n\n\n Mammalian Genome, 26: 413–421. 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{ring2015mouse,\n  title={A mouse informatics platform for phenotypic and translational discovery},\n  author={Ring, Natalie and Meehan, Terrence F and Blake, Andrew and Brown, James and Chen, Chao-Kung and Conte, Nathalie and Di Fenza, Armida and Fiegel, Tanja and Horner, Neil and Jacobsen, Julius OB and others},\n  journal={Mammalian Genome},\n  volume={26},\n  pages={413--421},\n  year={2015},\n  publisher={Springer US}\n}\n\n
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\n \n\n \n \n \n \n \n Analysis of 3D embryo data for the International Mouse Phenotyping Consortium.\n \n \n \n\n\n \n Horner, N. R; Brown, J. M; Barton, T. K; Cleak, J.; Johnson, S.; Szoke-Kovacs, Z.; Teboul, L.; Westerberg, C. H.; and Mallon, A.\n\n\n \n\n\n\n In GENETICS RESEARCH, volume 97, 2015. CAMBRIDGE UNIV PRESS 32 AVENUE OF THE AMERICAS, NEW YORK, NY 10013-2473 USA\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{horner2015analysis,\n  title={Analysis of 3D embryo data for the International Mouse Phenotyping Consortium},\n  author={Horner, Neil R and Brown, James M and Barton, Tobias K and Cleak, James and Johnson, Sara and Szoke-Kovacs, Zsombor and Teboul, Lydia and Westerberg, Carl Henrik and Mallon, Ann-Marie},\n  booktitle={GENETICS RESEARCH},\n  volume={97},\n  year={2015},\n  organization={CAMBRIDGE UNIV PRESS 32 AVENUE OF THE AMERICAS, NEW YORK, NY 10013-2473 USA}\n}\n\n
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\n \n\n \n \n \n \n \n Abstracts of papers presented at the 26th Genetics Society's Mammalian Genetics and Development Workshop held at the Institute of Child Health, University College London on 20th November 2015.\n \n \n \n\n\n \n LEE, K. K.; PESKETT, E.; STANIER, P.; PAUWS, E.; WILLIAMSON, I.; LETTICE, L.; HILL, R. E; BICKMORE, W. A; CUCKOVIC, D.; SEPPALA, M.; and others\n\n\n \n\n\n\n Genetics Research, 97. 2015.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{lee2015abstracts,\n  title={Abstracts of papers presented at the 26th Genetics Society's Mammalian Genetics and Development Workshop held at the Institute of Child Health, University College London on 20th November 2015.},\n  author={LEE, KEVIN KL and PESKETT, EMMA and STANIER, PHILIP and PAUWS, ERWIN and WILLIAMSON, IAIN and LETTICE, LAURA and HILL, ROBERT E and BICKMORE, WENDY A and CUCKOVIC, DORIS and SEPPALA, MAISA and others},\n  journal={Genetics Research},\n  volume={97},\n  year={2015},\n  publisher={Cambridge University Press}\n}\n\n
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\n  \n 2014\n \n \n (3)\n \n \n
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\n \n\n \n \n \n \n \n A J-linkage based approach for vanishing direction estimation in catadioptric images.\n \n \n \n\n\n \n Duan, W.; and Allinson, N.\n\n\n \n\n\n\n In 2014 22nd International Conference on Pattern Recognition, pages 2113–2118, 2014. IEEE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{duan2014j,\n  title={A J-linkage based approach for vanishing direction estimation in catadioptric images},\n  author={Duan, Wenting and Allinson, Nigel},\n  booktitle={2014 22nd International Conference on Pattern Recognition},\n  pages={2113--2118},\n  year={2014},\n  organization={IEEE}\n}\n\n
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\n \n\n \n \n \n \n \n A J-linkage based approach for vanishing direction estimation in catadioptric images.\n \n \n \n\n\n \n Allinson, N.; and Duan, W.\n\n\n \n\n\n\n . 2014.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{allinson2014j,\n  title={A J-linkage based approach for vanishing direction estimation in catadioptric images},\n  author={Allinson, Nigel and Duan, Wenting},\n  year={2014},\n  publisher={University of Lincoln}\n}\n\n
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\n \n\n \n \n \n \n \n 3D articulated registration of the mouse hind limb for bone morphometric analysis in rheumatoid arthritis.\n \n \n \n\n\n \n Brown, J. M; Naylor, A.; Buckley, C.; Filer, A.; and Claridge, E.\n\n\n \n\n\n\n In Biomedical Image Registration: 6th International Workshop, WBIR 2014, London, UK, July 7-8, 2014. Proceedings 6, pages 41–50, 2014. Springer International Publishing\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{brown20143d,\n  title={3D articulated registration of the mouse hind limb for bone morphometric analysis in rheumatoid arthritis},\n  author={Brown, James M and Naylor, Amy and Buckley, Chris and Filer, Andrew and Claridge, Ela},\n  booktitle={Biomedical Image Registration: 6th International Workshop, WBIR 2014, London, UK, July 7-8, 2014. Proceedings 6},\n  pages={41--50},\n  year={2014},\n  organization={Springer International Publishing}\n}\n\n
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\n  \n 2013\n \n \n (4)\n \n \n
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\n \n\n \n \n \n \n \n Relating vanishing points to catadioptric camera calibration.\n \n \n \n\n\n \n Duan, W.; Zhang, H.; and Allinson, N. M\n\n\n \n\n\n\n In Intelligent Robots and Computer Vision XXX: Algorithms and Techniques, volume 8662, pages 87–95, 2013. SPIE\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{duan2013relating,\n  title={Relating vanishing points to catadioptric camera calibration},\n  author={Duan, Wenting and Zhang, Hui and Allinson, Nigel M},\n  booktitle={Intelligent Robots and Computer Vision XXX: Algorithms and Techniques},\n  volume={8662},\n  pages={87--95},\n  year={2013},\n  organization={SPIE}\n}\n\n
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\n \n\n \n \n \n \n \n Fast vanishing points detection for omnidirectional images.\n \n \n \n\n\n \n Allinson, N.; and Duan, W.\n\n\n \n\n\n\n . 2013.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{allinson2013fast,\n  title={Fast vanishing points detection for omnidirectional images},\n  author={Allinson, Nigel and Duan, Wenting},\n  year={2013},\n  publisher={University of Lincoln}\n}\n\n
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\n \n\n \n \n \n \n \n Automatic conic and line grouping for calibration of central catadioptric camera.\n \n \n \n\n\n \n Allinson, N.; and Duan, W.\n\n\n \n\n\n\n . 2013.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{allinson2013automatic,\n  title={Automatic conic and line grouping for calibration of central catadioptric camera},\n  author={Allinson, Nigel and Duan, Wenting},\n  year={2013},\n  publisher={University of Lincoln}\n}\n\n
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\n \n\n \n \n \n \n \n Automatic approach for rectifying building facades from a single uncalibrated image.\n \n \n \n\n\n \n Allinson, N.; and Duan, W.\n\n\n \n\n\n\n . 2013.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{allinson2013automatic,\n  title={Automatic approach for rectifying building facades from a single uncalibrated image},\n  author={Allinson, Nigel and Duan, Wenting},\n  year={2013},\n  publisher={University of Lincoln}\n}\n\n
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\n  \n 2012\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Fast Vanishing Points Detection for Omnidirectional Images.\n \n \n \n\n\n \n Duan, W.; and Allinson, N. M\n\n\n \n\n\n\n In Multimedia and Signal Processing: Second International Conference, CMSP 2012, Shanghai, China, December 7-9, 2012. Proceedings, pages 163–170, 2012. Springer Berlin Heidelberg\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{duan2012fast,\n  title={Fast Vanishing Points Detection for Omnidirectional Images},\n  author={Duan, Wenting and Allinson, Nigel M},\n  booktitle={Multimedia and Signal Processing: Second International Conference, CMSP 2012, Shanghai, China, December 7-9, 2012. Proceedings},\n  pages={163--170},\n  year={2012},\n  organization={Springer Berlin Heidelberg}\n}\n\n
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\n  \n 2011\n \n \n (2)\n \n \n
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\n \n\n \n \n \n \n \n Automatic conic and line grouping for calibration of central catadioptric camera.\n \n \n \n\n\n \n Duan, W.; and Allinson, N. M\n\n\n \n\n\n\n In International Conference on Computer Analysis of Images and Patterns, pages 68–75, 2011. Springer Berlin Heidelberg Berlin, Heidelberg\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{duan2011automatic,\n  title={Automatic conic and line grouping for calibration of central catadioptric camera},\n  author={Duan, Wenting and Allinson, Nigel M},\n  booktitle={International Conference on Computer Analysis of Images and Patterns},\n  pages={68--75},\n  year={2011},\n  organization={Springer Berlin Heidelberg Berlin, Heidelberg}\n}\n\n
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\n \n\n \n \n \n \n \n Vanishing points detection and camera calibration.\n \n \n \n\n\n \n Duan, W.\n\n\n \n\n\n\n Ph.D. Thesis, University of Sheffield, 2011.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@phdthesis{duan2011vanishing,\n  title={Vanishing points detection and camera calibration},\n  author={Duan, Wenting},\n  year={2011},\n  school={University of Sheffield}\n}\n\n
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\n  \n 2010\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Vanishing points detection and line grouping for complex building facade identification.\n \n \n \n\n\n \n Duan, W.; and Allinson, N. M\n\n\n \n\n\n\n . 2010.\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{duan2010vanishing,\n  title={Vanishing points detection and line grouping for complex building facade identification},\n  author={Duan, Wenting and Allinson, Nigel M},\n  year={2010},\n  publisher={V{\\'a}clav Skala-UNION Agency}\n}\n\n
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\n  \n 2009\n \n \n (1)\n \n \n
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\n \n\n \n \n \n \n \n Automatic approach for rectifying building facades from a single uncalibrated image.\n \n \n \n\n\n \n Duan, W.; and Allinson, N. M\n\n\n \n\n\n\n In International Conference on Informatics in Control, Automation and Robotics, volume 1, pages 37–43, 2009. SCITEPRESS\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@inproceedings{duan2009automatic,\n  title={Automatic approach for rectifying building facades from a single uncalibrated image},\n  author={Duan, Wenting and Allinson, Nigel M},\n  booktitle={International Conference on Informatics in Control, Automation and Robotics},\n  volume={1},\n  pages={37--43},\n  year={2009},\n  organization={SCITEPRESS}\n}\n\n
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\n \n\n \n \n \n \n \n Transfer learning for automated polyp detection in video colonoscopic frames.\n \n \n \n\n\n \n Wen, Y.; Zhang, L.; Duan, W.; and Ye, X.\n\n\n \n\n\n\n . .\n \n\n\n\n
\n\n\n\n \n\n \n\n \n link\n  \n \n\n bibtex\n \n\n \n\n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
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@article{wentransfer,\n  title={Transfer learning for automated polyp detection in video colonoscopic frames},\n  author={Wen, Yan and Zhang, Lei and Duan, Wenting and Ye, Xujiong}\n}\n\n
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\n \n\n \n \n \n \n \n Micro-CT analysis of bone destruction in mouse models of rheumatoid arthritis.\n \n \n \n\n\n \n Brown, J.; Naylor, A; Filer, A; Styles, I.; and Claridge, E\n\n\n \n\n\n\n . .\n \n\n\n\n
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@article{brownmicro,\n  title={Micro-CT analysis of bone destruction in mouse models of rheumatoid arthritis},\n  author={Brown, JM and Naylor, A and Filer, A and Styles, IB and Claridge, E}\n}\n\n
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\n \n\n \n \n \n \n \n Segmentation of Brain Metastatic Lesions in Magnetic Resonance Imaging using Deep Learning.\n \n \n \n\n\n \n Patel, J. B; Beers, A. L; Chang, K.; Brown, J. M; Hoebel, K. V; Rosen, B. R; Huang, R. Y; Brastianos, P.; Gerstner, E. R; and Kalpathy-Cramer, J.\n\n\n \n\n\n\n . .\n \n\n\n\n
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@article{patelsegmentation,\n  title={Segmentation of Brain Metastatic Lesions in Magnetic Resonance Imaging using Deep Learning},\n  author={Patel, Jay B and Beers, Andrew L and Chang, Ken and Brown, James M and Hoebel, Katharina V and Rosen, Bruce R and Huang, Raymond Y and Brastianos, Priscilla and Gerstner, Elizabeth R and Kalpathy-Cramer, Jayashree}\n}\n\n
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\n \n\n \n \n \n \n \n Repeatability of radiomics features in double baseline MR imaging of glioblastoma.\n \n \n \n\n\n \n Hoebel, K. V; Beers, A. L; Brown, J. M; Chang, K.; Patel, J. B; Pinho, M. C; Rosen, B. R; Batchelor, T. T; Gerstner, E. R; and Kalpathy-Cramer, J.\n\n\n \n\n\n\n . .\n \n\n\n\n
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@article{hoebelrepeatability,\n  title={Repeatability of radiomics features in double baseline MR imaging of glioblastoma},\n  author={Hoebel, Katharina V and Beers, Andrew L and Brown, James M and Chang, Ken and Patel, Jay B and Pinho, Marco C and Rosen, Bruce R and Batchelor, Tracy T and Gerstner, Elizabeth R and Kalpathy-Cramer, Jayashree}\n}\n\n
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