var bibbase_data = {"data":"\"Loading..\"\n\n
\n\n \n\n \n\n \n \n\n \n\n \n \n\n \n\n \n
\n generated by\n \n \"bibbase.org\"\n\n \n
\n \n\n
\n\n \n\n\n
\n\n Excellent! Next you can\n create a new website with this list, or\n embed it in an existing web page by copying & pasting\n any of the following snippets.\n\n
\n JavaScript\n (easiest)\n
\n \n <script src=\"https://bibbase.org/show?bib=https%3A%2F%2Fmcintoshml.github.io%2Fcitations.bib&commas=true&jsonp=1&jsonp=1\"></script>\n \n
\n\n PHP\n
\n \n <?php\n $contents = file_get_contents(\"https://bibbase.org/show?bib=https%3A%2F%2Fmcintoshml.github.io%2Fcitations.bib&commas=true&jsonp=1\");\n print_r($contents);\n ?>\n \n
\n\n iFrame\n (not recommended)\n
\n \n <iframe src=\"https://bibbase.org/show?bib=https%3A%2F%2Fmcintoshml.github.io%2Fcitations.bib&commas=true&jsonp=1\"></iframe>\n \n
\n\n

\n For more details see the documention.\n

\n
\n
\n\n
\n\n This is a preview! To use this list on your own web site\n or create a new web site from it,\n create a free account. The file will be added\n and you will be able to edit it in the File Manager.\n We will show you instructions once you've created your account.\n
\n\n
\n\n

To the site owner:

\n\n

Action required! Mendeley is changing its\n API. In order to keep using Mendeley with BibBase past April\n 14th, you need to:\n

    \n
  1. renew the authorization for BibBase on Mendeley, and
    2. \n
  2. update the BibBase URL\n in your page the same way you did when you initially set up\n this page.\n
    3. \n
\n

\n\n

\n \n \n Fix it now\n

\n
\n\n
\n\n\n
\n \n \n
\n
\n  \n 2023\n \n \n (6)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Method and system for automated quality assurance in radiation therapy.\n \n \n \n\n\n \n Purdie, T. G, McIntosh, C. J., & Svistoun, I.\n\n\n \n\n\n\n August 22 2023.\n US Patent 11,735,309\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
\n 
@misc{purdie2023method,\n  title={Method and system for automated quality assurance in radiation therapy},\n  author={Purdie, Thomas G and McIntosh, Christopher James and Svistoun, Igor},\n  year={2023},\n  month=aug # "~22",\n  note={US Patent 11,735,309}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Comprehensive Cardiovascular Magnetic Resonance Tissue Characterization and Cardiotoxicity in Women With Breast Cancer.\n \n \n \n\n\n \n Thavendiranathan, P., Shalmon, T., Fan, C. S., Houbois, C., Amir, E., Thevakumaran, Y., Somerset, E., Malowany, J. M, Urzua-Fresno, C., Yip, P., & others\n\n\n \n\n\n\n JAMA cardiology. 2023.\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
\n 
@article{thavendiranathan2023comprehensive,\n  title={Comprehensive Cardiovascular Magnetic Resonance Tissue Characterization and Cardiotoxicity in Women With Breast Cancer},\n  author={Thavendiranathan, Paaladinesh and Shalmon, Tamar and Fan, Chun-Po Steve and Houbois, Christian and Amir, Eitan and Thevakumaran, Yobiga and Somerset, Emily and Malowany, Julia M and Urzua-Fresno, Camila and Yip, Paul and others},\n  journal={JAMA cardiology},\n  year={2023}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Machine Learning Radiotherapy Automated Planning: Transition to an Ultra-hypofractionated Prostate Model.\n \n \n \n\n\n \n Wan, V., Ramchand, E., Khalifa, A., Conroy, L., McIntosh, C., Purdie, T. G, Tsui, G., Tadic, T., & Winter, J.\n\n\n \n\n\n\n Journal of Medical Imaging and Radiation Sciences, 54(1): 10. 2023.\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
\n 
@article{wan2023machine,\n  title={Machine Learning Radiotherapy Automated Planning: Transition to an Ultra-hypofractionated Prostate Model},\n  author={Wan, Vanessa and Ramchand, Emily and Khalifa, Aly and Conroy, Leigh and McIntosh, Chris and Purdie, Thomas G and Tsui, Grace and Tadic, Tony and Winter, Jeff},\n  journal={Journal of Medical Imaging and Radiation Sciences},\n  volume={54},\n  number={1},\n  pages={10},\n  year={2023},\n  publisher={Elsevier}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Multi-institutional prognostic modelling in head and neck cancer: evaluating impact and generalizability of deep learning and radiomics.\n \n \n \n\n\n \n Kazmierski, M., Welch, M., Kim, S., McIntosh, C., Rey-McIntyre, K., Huang, S. H., Patel, T., Tadic, T., Milosevic, M., Liu, F., & others\n\n\n \n\n\n\n Cancer Research Communications,CRC–22. 2023.\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
\n 
@article{kazmierski2023multi,\n  title={Multi-institutional prognostic modelling in head and neck cancer: evaluating impact and generalizability of deep learning and radiomics},\n  author={Kazmierski, Michal and Welch, Mattea and Kim, Sejin and McIntosh, Chris and Rey-McIntyre, Katrina and Huang, Shao Hui and Patel, Tirth and Tadic, Tony and Milosevic, Michael and Liu, Fei-Fei and others},\n  journal={Cancer Research Communications},\n  pages={CRC--22},\n  year={2023},\n  publisher={American Association for Cancer Research}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Machine Learning for Prediction of Adverse Cardiovascular Events in Adults With Repaired Tetralogy of Fallot Using Clinical and Cardiovascular Magnetic Resonance Imaging Variables.\n \n \n \n\n\n \n Ishikita, A., McIntosh, C., Hanneman, K., Lee, M. M, Liang, T., Karur, G. R, Roche, S L., Hickey, E., Geva, T., Barron, D. J, & others\n\n\n \n\n\n\n Circulation: Cardiovascular Imaging, 16(6): e015205. 2023.\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
\n 
@article{ishikita2023machine,\n  title={Machine Learning for Prediction of Adverse Cardiovascular Events in Adults With Repaired Tetralogy of Fallot Using Clinical and Cardiovascular Magnetic Resonance Imaging Variables},\n  author={Ishikita, Ayako and McIntosh, Chris and Hanneman, Kate and Lee, Myunghyun M and Liang, Tiffany and Karur, Gauri R and Roche, S Lucy and Hickey, Edward and Geva, Tal and Barron, David J and others},\n  journal={Circulation: Cardiovascular Imaging},\n  volume={16},\n  number={6},\n  pages={e015205},\n  year={2023},\n  publisher={Lippincott Williams \\& Wilkins Hagerstown, MD}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Cross-Task Attention Network: Improving Multi-Task Learning for Medical Imaging Applications.\n \n \n \n\n\n \n Kim, S., Purdie, T. G, & McIntosh, C.\n\n\n \n\n\n\n arXiv preprint arXiv:2309.03837. 2023.\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
\n 
@article{kim2023cross,\n  title={Cross-Task Attention Network: Improving Multi-Task Learning for Medical Imaging Applications},\n  author={Kim, Sangwook and Purdie, Thomas G and McIntosh, Chris},\n  journal={arXiv preprint arXiv:2309.03837},\n  year={2023}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2022\n \n \n (16)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Understanding machine learning classifier decisions in automated radiotherapy quality assurance.\n \n \n \n\n\n \n Chen, Y., Aleman, D. M, Purdie, T. G, & McIntosh, C.\n\n\n \n\n\n\n Physics in Medicine & Biology, 67(2): 025001. 2022.\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
\n 
@article{chen2022understanding,\n  title={Understanding machine learning classifier decisions in automated radiotherapy quality assurance},\n  author={Chen, Yunsheng and Aleman, Dionne M and Purdie, Thomas G and McIntosh, Chris},\n  journal={Physics in Medicine \\& Biology},\n  volume={67},\n  number={2},\n  pages={025001},\n  year={2022},\n  publisher={IOP Publishing}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n A pilot study of machine-learning based automated planning for primary brain tumours.\n \n \n \n\n\n \n Tsang, D. S, Tsui, G., McIntosh, C., Purdie, T., Bauman, G., Dama, H., Laperriere, N., Millar, B., Shultz, D. B, Ahmed, S., & others\n\n\n \n\n\n\n Radiation Oncology, 17(1): 3. 2022.\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
\n 
@article{tsang2022pilot,\n  title={A pilot study of machine-learning based automated planning for primary brain tumours},\n  author={Tsang, Derek S and Tsui, Grace and McIntosh, Chris and Purdie, Thomas and Bauman, Glenn and Dama, Hitesh and Laperriere, Normand and Millar, Barbara-Ann and Shultz, David B and Ahmed, Sameera and others},\n  journal={Radiation Oncology},\n  volume={17},\n  number={1},\n  pages={3},\n  year={2022},\n  publisher={BioMed Central London}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Cardiovascular signatures of COVID-19 predict mortality and identify barrier stabilizing therapies.\n \n \n \n\n\n \n Gustafson, D., Ngai, M., Wu, R., Hou, H., Schoffel, A. C., Erice, C., Mandla, S., Billia, F., Wilson, M. D, Radisic, M., & others\n\n\n \n\n\n\n EBioMedicine, 78. 2022.\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
\n 
@article{gustafson2022cardiovascular,\n  title={Cardiovascular signatures of COVID-19 predict mortality and identify barrier stabilizing therapies},\n  author={Gustafson, Dakota and Ngai, Michelle and Wu, Ruilin and Hou, Huayun and Schoffel, Alice Carvalhal and Erice, Clara and Mandla, Serena and Billia, Filio and Wilson, Michael D and Radisic, Milica and others},\n  journal={EBioMedicine},\n  volume={78},\n  year={2022},\n  publisher={Elsevier}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n SuPART: supervised projective adapted resonance theory for automatic quality assurance approval of radiotherapy treatment plans.\n \n \n \n\n\n \n Kamran, H., Aleman, D. M, McIntosh, C., & Purdie, T. G\n\n\n \n\n\n\n Physics in Medicine & Biology, 67(6): 065004. 2022.\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
\n 
@article{kamran2022supart,\n  title={SuPART: supervised projective adapted resonance theory for automatic quality assurance approval of radiotherapy treatment plans},\n  author={Kamran, Hootan and Aleman, Dionne M and McIntosh, Chris and Purdie, Thomas G},\n  journal={Physics in Medicine \\& Biology},\n  volume={67},\n  number={6},\n  pages={065004},\n  year={2022},\n  publisher={IOP Publishing}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Domain adaptation of automated treatment planning from computed tomography to magnetic resonance.\n \n \n \n\n\n \n Khalifa, A., Winter, J., Navarro, I., McIntosh, C., & Purdie, T. G\n\n\n \n\n\n\n Physics in Medicine & Biology, 67(12): 125010. 2022.\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
\n 
@article{khalifa2022domain,\n  title={Domain adaptation of automated treatment planning from computed tomography to magnetic resonance},\n  author={Khalifa, Aly and Winter, Jeff and Navarro, Inmaculada and McIntosh, Chris and Purdie, Thomas G},\n  journal={Physics in Medicine \\& Biology},\n  volume={67},\n  number={12},\n  pages={125010},\n  year={2022},\n  publisher={IOP Publishing}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n A MACHINE LEARNING ANALYSIS OF THERAPEUTIC COMPONENTS OF DIGITAL COUNSELING FOR HEART FAILURE.\n \n \n \n\n\n \n Nolan, R. P, Peikari, M., Fan, C. S., Fezza, G. C, Ross, H. J., & McIntosh, C.\n\n\n \n\n\n\n Journal of the American College of Cardiology, 79(9_Supplement): 2044–2044. 2022.\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
\n 
@article{nolan2022machine,\n  title={A MACHINE LEARNING ANALYSIS OF THERAPEUTIC COMPONENTS OF DIGITAL COUNSELING FOR HEART FAILURE},\n  author={Nolan, Robert P and Peikari, Mohammad and Fan, Chun-Po Steve and Fezza, Gabriel C and Ross, Heather Joan and McIntosh, Chris},\n  journal={Journal of the American College of Cardiology},\n  volume={79},\n  number={9\\_Supplement},\n  pages={2044--2044},\n  year={2022},\n  publisher={American College of Cardiology Foundation Washington DC}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Artificial intelligence for the prognostication and management of heart transplant: a scoping review.\n \n \n \n\n\n \n Giacobbo, S, Murray, K., Moayedi, Y, Posada, J D., McIntosh, C, Ross, H., & Foroutan, F\n\n\n \n\n\n\n The Journal of Heart and Lung Transplantation, 41(4): S219. 2022.\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
\n 
@article{giacobbo2022artificial,\n  title={Artificial intelligence for the prognostication and management of heart transplant: a scoping review},\n  author={Giacobbo, S and Murray, KR and Moayedi, Y and Posada, J Duero and McIntosh, C and Ross, HJ and Foroutan, F},\n  journal={The Journal of Heart and Lung Transplantation},\n  volume={41},\n  number={4},\n  pages={S219},\n  year={2022},\n  publisher={Elsevier}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n PD-0894 atlas-based treatment planning models for magnetic resonance guided therapy.\n \n \n \n\n\n \n Khalifa, A, Winter, J, Navarro, I, McIntosh, C, & Purdie, T.\n\n\n \n\n\n\n Radiotherapy and Oncology, 170: S786–S787. 2022.\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
\n 
@article{khalifa2022pd,\n  title={PD-0894 atlas-based treatment planning models for magnetic resonance guided therapy},\n  author={Khalifa, A and Winter, J and Navarro, I and McIntosh, C and Purdie, TG},\n  journal={Radiotherapy and Oncology},\n  volume={170},\n  pages={S786--S787},\n  year={2022},\n  publisher={Elsevier}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n PO-1256 Multi-domain automated lung segmentation for inflammatory lung disease (ILD) detection.\n \n \n \n\n\n \n Hope, A, McIntosh, C, Welch, M, Kandel, S, Purdie, T, Tadic, T, & Patel, T\n\n\n \n\n\n\n Radiotherapy and Oncology, 170: S1061. 2022.\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
\n 
@article{hope2022po,\n  title={PO-1256 Multi-domain automated lung segmentation for inflammatory lung disease (ILD) detection},\n  author={Hope, A and McIntosh, C and Welch, M and Kandel, S and Purdie, T and Tadic, T and Patel, T},\n  journal={Radiotherapy and Oncology},\n  volume={170},\n  pages={S1061},\n  year={2022},\n  publisher={Elsevier}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Validation of CBCT-Based Machine-Learning Automated Planning for Adaptive Prostate Radiation Therapy.\n \n \n \n\n\n \n Khalifa, A, Golshan, M, Navarro, I, Malkov, V, McIntosh, C, Purdie, T, Tadic, T, & Winter, J\n\n\n \n\n\n\n In MEDICAL PHYSICS, volume 49, pages E246–E246, 2022. WILEY 111 RIVER ST, HOBOKEN 07030-5774, NJ 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
\n 
@inproceedings{khalifa2022validation,\n  title={Validation of CBCT-Based Machine-Learning Automated Planning for Adaptive Prostate Radiation Therapy},\n  author={Khalifa, A and Golshan, M and Navarro, I and Malkov, V and McIntosh, C and Purdie, T and Tadic, T and Winter, J},\n  booktitle={MEDICAL PHYSICS},\n  volume={49},\n  number={6},\n  pages={E246--E246},\n  year={2022},\n  organization={WILEY 111 RIVER ST, HOBOKEN 07030-5774, NJ USA}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Daily Adaptive Replanning with Dose Accumulation for Prostate Ultra-Hypofractionated Radiotherapy Using Machine Learning Automated Planning On CBCT.\n \n \n \n\n\n \n Golshan, M, Khalifa, A, Winter, J, Xie, J, McIntosh, C, Purdie, T, Malkov, V, & Tadic, T\n\n\n \n\n\n\n In MEDICAL PHYSICS, volume 49, pages E465–E466, 2022. WILEY 111 RIVER ST, HOBOKEN 07030-5774, NJ 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
\n 
@inproceedings{golshan2022daily,\n  title={Daily Adaptive Replanning with Dose Accumulation for Prostate Ultra-Hypofractionated Radiotherapy Using Machine Learning Automated Planning On CBCT},\n  author={Golshan, M and Khalifa, A and Winter, J and Xie, J and McIntosh, C and Purdie, T and Malkov, V and Tadic, T},\n  booktitle={MEDICAL PHYSICS},\n  volume={49},\n  number={6},\n  pages={E465--E466},\n  year={2022},\n  organization={WILEY 111 RIVER ST, HOBOKEN 07030-5774, NJ USA}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Machine learning using simple non-invasive tests of fibrosis and B-mode ultrasound for the prediction of adverse liver-related outcomes in NAFLD.\n \n \n \n\n\n \n Kosick, H. M, McIntosh, C., Fakhriyehasl, M., Bera, C., Adeyi, O., Jhaveri, K., & Patel, K.\n\n\n \n\n\n\n Journal of Hepatology, 77: S429–S430. 2022.\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
\n 
@article{kosick2022machine,\n  title={Machine learning using simple non-invasive tests of fibrosis and B-mode ultrasound for the prediction of adverse liver-related outcomes in NAFLD},\n  author={Kosick, Heather M and McIntosh, Chris and Fakhriyehasl, Mina and Bera, Chinmay and Adeyi, Oyedele and Jhaveri, Kartik and Patel, Keyur},\n  journal={Journal of Hepatology},\n  volume={77},\n  pages={S429--S430},\n  year={2022},\n  publisher={Elsevier}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n EP1225: MACHINE LEARNING ALGORITHMS FOR PREDICTION OF NASH AND ADVANCED FIBROSIS IN NAFLD PATIENTS.\n \n \n \n\n\n \n Kosick, H. M, McIntosh, C., Fakhriyehasl, M., Bera, C., Adeyi, O., Jhaveri, K., & Patel, K.\n\n\n \n\n\n\n Gastroenterology, 162(7): S–1293. 2022.\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
\n 
@article{kosick2022ep1225,\n  title={EP1225: MACHINE LEARNING ALGORITHMS FOR PREDICTION OF NASH AND ADVANCED FIBROSIS IN NAFLD PATIENTS},\n  author={Kosick, Heather M and McIntosh, Chris and Fakhriyehasl, Mina and Bera, Chinmay and Adeyi, Oyedele and Jhaveri, Kartik and Patel, Keyur},\n  journal={Gastroenterology},\n  volume={162},\n  number={7},\n  pages={S--1293},\n  year={2022},\n  publisher={WB Saunders}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Validation of a daily adaptive radiation therapy pipeline incorporating machine learning automated treatment planning on CBCT with dose accumulation.\n \n \n \n\n\n \n Khalifa, A., Golshan, M., Navarro, I., Xie, J., McIntosh, C., Purdie, T. G, Malkov, V., Tadic, T., & Winter, J.\n\n\n \n\n\n\n In MEDICAL PHYSICS, volume 49, pages 5638–5638, 2022. WILEY 111 RIVER ST, HOBOKEN 07030-5774, NJ 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
\n 
@inproceedings{khalifa2022validation,\n  title={Validation of a daily adaptive radiation therapy pipeline incorporating machine learning automated treatment planning on CBCT with dose accumulation},\n  author={Khalifa, Aly and Golshan, Maryam and Navarro, Inmaculada and Xie, Jason and McIntosh, Chris and Purdie, Thomas G and Malkov, Victor and Tadic, Tony and Winter, Jeff},\n  booktitle={MEDICAL PHYSICS},\n  volume={49},\n  number={8},\n  pages={5638--5638},\n  year={2022},\n  organization={WILEY 111 RIVER ST, HOBOKEN 07030-5774, NJ USA}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Creation of an Artificial Intelligence Model For Prediction of Major Adverse Cardiovascular Events Late After Tetralogy of Fallot Repair.\n \n \n \n\n\n \n Ishikita, A., McIntosh, C., Lee, M. M, Raptis, S., Liang, T., Hanneman, K. A, Karur, G., Roche, S. L, Barron, D., Hickey, E., & others\n\n\n \n\n\n\n Circulation, 146(Suppl_1): A12563–A12563. 2022.\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
\n 
@article{ishikita2022creation,\n  title={Creation of an Artificial Intelligence Model For Prediction of Major Adverse Cardiovascular Events Late After Tetralogy of Fallot Repair},\n  author={Ishikita, Ayako and McIntosh, Chris and Lee, Myunghyun M and Raptis, Stavroula and Liang, Tiffany and Hanneman, Kate A and Karur, Gauri and Roche, Susan L and Barron, David and Hickey, Edward and others},\n  journal={Circulation},\n  volume={146},\n  number={Suppl\\_1},\n  pages={A12563--A12563},\n  year={2022},\n  publisher={Lippincott Williams \\& Wilkins Hagerstown, MD}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n A Comprehensive Study of Radiomics-based Machine Learning for Fibrosis Detection.\n \n \n \n\n\n \n Yoo, J. J, Namdar, K., McIntosh, C., Khalvati, F., & Rogalla, P.\n\n\n \n\n\n\n arXiv preprint arXiv:2211.14396. 2022.\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
\n 
@article{yoo2022comprehensive,\n  title={A Comprehensive Study of Radiomics-based Machine Learning for Fibrosis Detection},\n  author={Yoo, Jay J and Namdar, Khashayar and McIntosh, Chris and Khalvati, Farzad and Rogalla, Patrik},\n  journal={arXiv preprint arXiv:2211.14396},\n  year={2022}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2021\n \n \n (10)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Analytics methods and tools for integration of biomedical data in medicine.\n \n \n \n\n\n \n Zhang, L., Karimzadeh, M., Welch, M., McIntosh, C., & Wang, B.\n\n\n \n\n\n\n In Artificial Intelligence in Medicine, pages 113–129. Academic Press, 2021.\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
\n 
@incollection{zhang2021analytics,\n  title={Analytics methods and tools for integration of biomedical data in medicine},\n  author={Zhang, Lin and Karimzadeh, Mehran and Welch, Mattea and McIntosh, Chris and Wang, Bo},\n  booktitle={Artificial Intelligence in Medicine},\n  pages={113--129},\n  year={2021},\n  publisher={Academic Press}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n A Machine Learning Challenge for Prognostic Modelling in Head and Neck Cancer Using Multi-modal Data.\n \n \n \n\n\n \n Kazmierski, M., Welch, M., Kim, S., McIntosh, C., Head, P. M., Group, N. C., Rey-McIntyre, K., Huang, S. H., Patel, T., Tadic, T., & others\n\n\n \n\n\n\n arXiv preprint arXiv:2101.11935. 2021.\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
\n 
@article{kazmierski2021machine,\n  title={A Machine Learning Challenge for Prognostic Modelling in Head and Neck Cancer Using Multi-modal Data},\n  author={Kazmierski, Michal and Welch, Mattea and Kim, Sejin and McIntosh, Chris and Head, Princess Margaret and Group, Neck Cancer and Rey-McIntyre, Katrina and Huang, Shao Hui and Patel, Tirth and Tadic, Tony and others},\n  journal={arXiv preprint arXiv:2101.11935},\n  year={2021}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n A Machine Learning Challenge for Prognostic Modelling in Head and Neck Cancer Using Multi-modal Data.\n \n \n \n\n\n \n Haibe-Kains, B., Kazmierski, M., Welch, M., Kim, S., McIntosh, C., Rey-McIntyre, K., Huang, S. H., Patel, T., Tadic, T., Milosevic, M., & others\n\n\n \n\n\n\n . 2021.\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
\n 
@article{haibe2021machine,\n  title={A Machine Learning Challenge for Prognostic Modelling in Head and Neck Cancer Using Multi-modal Data},\n  author={Haibe-Kains, Benjamin and Kazmierski, Michal and Welch, Mattea and Kim, Sejin and McIntosh, Chris and Rey-McIntyre, Katrina and Huang, Shao Hui and Patel, Tirth and Tadic, Tony and Milosevic, Michael and others},\n  year={2021}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Mass spectrometry imaging reveals a gradient of cancer-like metabolic states in the vicinity of cancer not seen in morphometric margins from microscopy.\n \n \n \n\n\n \n Woolman, M., Katz, L., Gopinath, G., Kiyota, T., Kuzan-Fischer, C. M, Ferry, I., Zaidi, M., Peters, K., Aman, A., McKee, T., & others\n\n\n \n\n\n\n Analytical chemistry, 93(10): 4408–4416. 2021.\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
\n 
@article{woolman2021mass,\n  title={Mass spectrometry imaging reveals a gradient of cancer-like metabolic states in the vicinity of cancer not seen in morphometric margins from microscopy},\n  author={Woolman, Michael and Katz, Lauren and Gopinath, Georgia and Kiyota, Taira and Kuzan-Fischer, Claudia M and Ferry, Isabelle and Zaidi, Mark and Peters, Kaitlyn and Aman, Ahmed and McKee, Trevor and others},\n  journal={Analytical chemistry},\n  volume={93},\n  number={10},\n  pages={4408--4416},\n  year={2021},\n  publisher={American Chemical Society}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Clinical integration of machine learning for curative-intent radiation treatment of patients with prostate cancer.\n \n \n \n\n\n \n McIntosh, C., Conroy, L., Tjong, M. C, Craig, T., Bayley, A., Catton, C., Gospodarowicz, M., Helou, J., Isfahanian, N., Kong, V., & others\n\n\n \n\n\n\n Nature medicine, 27(6): 999–1005. 2021.\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
\n 
@article{mcintosh2021clinical,\n  title={Clinical integration of machine learning for curative-intent radiation treatment of patients with prostate cancer},\n  author={McIntosh, Chris and Conroy, Leigh and Tjong, Michael C and Craig, Tim and Bayley, Andrew and Catton, Charles and Gospodarowicz, Mary and Helou, Joelle and Isfahanian, Naghmeh and Kong, Vickie and others},\n  journal={Nature medicine},\n  volume={27},\n  number={6},\n  pages={999--1005},\n  year={2021},\n  publisher={Nature Publishing Group US New York}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Automated Machine-Learning Radiotherapy Planning for Pediatric and Adult Brain Tumours.\n \n \n \n\n\n \n Tsui, G., Tsang, D. S, McIntosh, C., Purdie, T. G, Bauman, G., Laperriere, N., Dama, H., Khandwala, M., & Hodgson, D. C\n\n\n \n\n\n\n Journal of Medical Imaging and Radiation Sciences, 52(2): S3. 2021.\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
\n 
@article{tsui2021automated,\n  title={Automated Machine-Learning Radiotherapy Planning for Pediatric and Adult Brain Tumours},\n  author={Tsui, Grace and Tsang, Derek S and McIntosh, Chris and Purdie, Thomas G and Bauman, Glenn and Laperriere, Normand and Dama, Hitesh and Khandwala, Mohammad and Hodgson, David C},\n  journal={Journal of Medical Imaging and Radiation Sciences},\n  volume={52},\n  number={2},\n  pages={S3},\n  year={2021},\n  publisher={Elsevier}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Performance stability evaluation of atlas-based machine learning radiation therapy treatment planning in prostate cancer.\n \n \n \n\n\n \n Conroy, L., Khalifa, A., Berlin, A., McIntosh, C., & Purdie, T. G\n\n\n \n\n\n\n Physics in Medicine & Biology, 66(13): 134001. 2021.\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
\n 
@article{conroy2021performance,\n  title={Performance stability evaluation of atlas-based machine learning radiation therapy treatment planning in prostate cancer},\n  author={Conroy, Leigh and Khalifa, Aly and Berlin, Alejandro and McIntosh, Chris and Purdie, Thomas G},\n  journal={Physics in Medicine \\& Biology},\n  volume={66},\n  number={13},\n  pages={134001},\n  year={2021},\n  publisher={IOP Publishing}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Letter by Wang et al Regarding Article,“Association Between Coffee Intake and Incident Heart Failure Risk: A Machine Learning Analysis of the FHS, the ARIC Study, and the CHS”.\n \n \n \n\n\n \n Wang, V. N, Fan, C. S., & McIntosh, C.\n\n\n \n\n\n\n Circulation: Heart Failure, 14(12): e008611. 2021.\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
\n 
@article{wang2021letter,\n  title={Letter by Wang et al Regarding Article,“Association Between Coffee Intake and Incident Heart Failure Risk: A Machine Learning Analysis of the FHS, the ARIC Study, and the CHS”},\n  author={Wang, Vicki N and Fan, Chun-Po Steve and McIntosh, Chris},\n  journal={Circulation: Heart Failure},\n  volume={14},\n  number={12},\n  pages={e008611},\n  year={2021},\n  publisher={Lippincott Williams \\& Wilkins Hagerstown, MD}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Remote Mobile Outpatient Monitoring in Transplant (Reboot) 2.0: Protocol for a Randomized Controlled Trial.\n \n \n \n\n\n \n Murray, K. R, Foroutan, F., Amadio, J. M, Posada, J. D., Kozuszko, S., Duhamel, J., Tsang, K., Farkouh, M. E, McDonald, M., Billia, F., & others\n\n\n \n\n\n\n JMIR Research Protocols, 10(10): e26816. 2021.\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
\n 
@article{murray2021remote,\n  title={Remote Mobile Outpatient Monitoring in Transplant (Reboot) 2.0: Protocol for a Randomized Controlled Trial},\n  author={Murray, Kevin R and Foroutan, Farid and Amadio, Jennifer M and Posada, Juan Duero and Kozuszko, Stella and Duhamel, Joseph and Tsang, Katherine and Farkouh, Michael E and McDonald, Michael and Billia, Filio and others},\n  journal={JMIR Research Protocols},\n  volume={10},\n  number={10},\n  pages={e26816},\n  year={2021},\n  publisher={JMIR Publications Inc., Toronto, Canada}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Remote Mobile Outpatient Monitoring in Transplant (Reboot) 2.0: Protocol for a Randomized Controlled Trial.\n \n \n \n\n\n \n Murray, K., Foroutan, F, Amadio, J., Posada, J., Kozuszko, S, Duhamel, J, Tsang, K, Farkouh, M., McDonald, M, Billia, F, & others\n\n\n \n\n\n\n JMIR Research Protocols, 10(10): e26816–e26816. 2021.\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
\n 
@article{murray2021remote,\n  title={Remote Mobile Outpatient Monitoring in Transplant (Reboot) 2.0: Protocol for a Randomized Controlled Trial.},\n  author={Murray, KR and Foroutan, F and Amadio, JM and Posada, JD and Kozuszko, S and Duhamel, J and Tsang, K and Farkouh, ME and McDonald, M and Billia, F and others},\n  journal={JMIR Research Protocols},\n  volume={10},\n  number={10},\n  pages={e26816--e26816},\n  year={2021}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2020\n \n \n (10)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Automatic classification of dental artifact status for efficient image veracity checks: effects of image resolution and convolutional neural network depth.\n \n \n \n\n\n \n Welch, M. L, McIntosh, C., Purdie, T. G, Wee, L., Traverso, A., Dekker, A., Haibe-Kains, B., & Jaffray, D. A\n\n\n \n\n\n\n Physics in Medicine & Biology, 65(1): 015005. 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
\n 
@article{welch2020automatic,\n  title={Automatic classification of dental artifact status for efficient image veracity checks: effects of image resolution and convolutional neural network depth},\n  author={Welch, Mattea L and McIntosh, Chris and Purdie, Tom G and Wee, Leonard and Traverso, Alberto and Dekker, Andre and Haibe-Kains, Benjamin and Jaffray, David A},\n  journal={Physics in Medicine \\& Biology},\n  volume={65},\n  number={1},\n  pages={015005},\n  year={2020},\n  publisher={IOP Publishing}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n External validation and transfer learning of convolutional neural networks for computed tomography dental artifact classification.\n \n \n \n\n\n \n Welch, M. L, McIntosh, C., Traverso, A., Wee, L., Purdie, T. G, Dekker, A., Haibe-Kains, B., & Jaffray, D. A\n\n\n \n\n\n\n Physics in Medicine & Biology, 65(3): 035017. 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
\n 
@article{welch2020external,\n  title={External validation and transfer learning of convolutional neural networks for computed tomography dental artifact classification},\n  author={Welch, Mattea L and McIntosh, Chris and Traverso, Alberto and Wee, Leonard and Purdie, Tom G and Dekker, Andre and Haibe-Kains, Benjamin and Jaffray, David A},\n  journal={Physics in Medicine \\& Biology},\n  volume={65},\n  number={3},\n  pages={035017},\n  year={2020},\n  publisher={IOP Publishing}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n User-controlled pipelines for feature integration and head and neck radiation therapy outcome predictions.\n \n \n \n\n\n \n Welch, M. L, McIntosh, C., McNiven, A., Huang, S. H., Zhang, B., Wee, L., Traverso, A., O'Sullivan, B., Hoebers, F., Dekker, A., & others\n\n\n \n\n\n\n Physica Medica, 70: 145–152. 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
\n 
@article{welch2020user,\n  title={User-controlled pipelines for feature integration and head and neck radiation therapy outcome predictions},\n  author={Welch, Mattea L and McIntosh, Chris and McNiven, Andrea and Huang, Shao Hui and Zhang, Bei-Bei and Wee, Leonard and Traverso, Alberto and O'Sullivan, Brian and Hoebers, Frank and Dekker, Andre and others},\n  journal={Physica Medica},\n  volume={70},\n  pages={145--152},\n  year={2020},\n  publisher={Elsevier}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Abstract P4-12-24: Evaluation of partial breast irradiation suitability in early stage breast cancer patients.\n \n \n \n\n\n \n Koch, C. A., Corey, G., Han, K., Lee, G., Purdie, T., McIntosh, C., Lindsay, P., Liu, F., Fyles, A., Levin, W., & others\n\n\n \n\n\n\n Cancer Research, 80(4_Supplement): P4–12. 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
\n 
@article{koch2020abstract,\n  title={Abstract P4-12-24: Evaluation of partial breast irradiation suitability in early stage breast cancer patients},\n  author={Koch, Christine Anne and Corey, Gemma and Han, Kathy and Lee, Grace and Purdie, Tom and McIntosh, Chris and Lindsay, Patricia and Liu, Fei-Fei and Fyles, Anthony and Levin, Wilf and others},\n  journal={Cancer Research},\n  volume={80},\n  number={4\\_Supplement},\n  pages={P4--12},\n  year={2020},\n  publisher={The American Association for Cancer Research}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Transparency and reproducibility in artificial intelligence.\n \n \n \n\n\n \n Haibe-Kains, B., Adam, G. A., Hosny, A., Khodakarami, F., of Directors Shraddha Thakkar 35 Kusko Rebecca 36 Sansone Susanna-Assunta 37 Tong Weida 35 Wolfinger Russ D. 38 Mason Christopher E. 39 Jones Wendell 40 Dopazo Joaquin 41 Furlanello Cesare 42, M. A. Q. C. (. S. B., Waldron, L., Wang, B., McIntosh, C., Goldenberg, A., Kundaje, A., & others\n\n\n \n\n\n\n Nature, 586(7829): E14–E16. 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
\n 
@article{haibe2020transparency,\n  title={Transparency and reproducibility in artificial intelligence},\n  author={Haibe-Kains, Benjamin and Adam, George Alexandru and Hosny, Ahmed and Khodakarami, Farnoosh and Massive Analysis Quality Control (MAQC) Society Board of Directors Shraddha Thakkar 35 Kusko Rebecca 36 Sansone Susanna-Assunta 37 Tong Weida 35 Wolfinger Russ D. 38 Mason Christopher E. 39 Jones Wendell 40 Dopazo Joaquin 41 Furlanello Cesare 42 and Waldron, Levi and Wang, Bo and McIntosh, Chris and Goldenberg, Anna and Kundaje, Anshul and others},\n  journal={Nature},\n  volume={586},\n  number={7829},\n  pages={E14--E16},\n  year={2020},\n  publisher={Nature Publishing Group UK London}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Cdf-net: Cross-domain fusion network for accelerated mri reconstruction.\n \n \n \n\n\n \n Nitski, O., Nag, S., McIntosh, C., & Wang, B.\n\n\n \n\n\n\n In International Conference on Medical Image Computing and Computer-Assisted Intervention, pages 421–430, 2020. Springer International Publishing Cham\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
\n 
@inproceedings{nitski2020cdf,\n  title={Cdf-net: Cross-domain fusion network for accelerated mri reconstruction},\n  author={Nitski, Osvald and Nag, Sayan and McIntosh, Chris and Wang, Bo},\n  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},\n  pages={421--430},\n  year={2020},\n  organization={Springer International Publishing Cham}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Automated machine-learning radiation therapy treatment planning for pediatric and adult brain tumors.\n \n \n \n\n\n \n Tsui, G, Tsang, D., McIntosh, C, Purdie, T., Khandwala, M, Bauman, G., Laperriere, N., Dama, H, & Hodgson, D\n\n\n \n\n\n\n International Journal of Radiation Oncology, Biology, Physics, 108(3): e777. 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
\n 
@article{tsui2020automated,\n  title={Automated machine-learning radiation therapy treatment planning for pediatric and adult brain tumors},\n  author={Tsui, G and Tsang, DSC and McIntosh, C and Purdie, TG and Khandwala, M and Bauman, GS and Laperriere, NJ and Dama, H and Hodgson, D},\n  journal={International Journal of Radiation Oncology, Biology, Physics},\n  volume={108},\n  number={3},\n  pages={e777},\n  year={2020},\n  publisher={Elsevier}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n 26: Automated Machine-Learning Radiotherapy Planning for Pediatric and Adult Brain Tumours.\n \n \n \n\n\n \n Tsui, G., Tsang, D., McIntosh, C., Purdie, T., Khandwala, M., Bauman, G., Laperriere, N., Dama, H., & Hodgson, D.\n\n\n \n\n\n\n Radiotherapy and Oncology, 150: S15. 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
\n 
@article{tsui202026,\n  title={26: Automated Machine-Learning Radiotherapy Planning for Pediatric and Adult Brain Tumours},\n  author={Tsui, Grace and Tsang, Derek and McIntosh, Chris and Purdie, Tom and Khandwala, Mohammad and Bauman, Glenn and Laperriere, Normand and Dama, Hitesh and Hodgson, David},\n  journal={Radiotherapy and Oncology},\n  volume={150},\n  pages={S15},\n  year={2020},\n  publisher={Elsevier}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n User-controlled pipelines for feature integration and head and neck radiation therapy outcome predictions.\n \n \n \n\n\n \n Traverso, A. T., Traverso, A., Dekker, A. D., Zhang, B. B. Z., Zhang, B. B., Huang, S. H. H., Huang, S. H., Welch, M. L W., McNiven, A. M., McNiven, A., & others\n\n\n \n\n\n\n . 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
\n 
@article{traverso2020user,\n  title={User-controlled pipelines for feature integration and head and neck radiation therapy outcome predictions},\n  author={Traverso, Alberto Traverso and Traverso, Alberto and Dekker, Andre Dekker and Zhang, Bei Bei Zhang and Zhang, Bei Bei and Huang, Shao Hui Huang and Huang, Shao Hui and Welch, Mattea L Welch and McNiven, Andrea McNiven and McNiven, Andrea and others},\n  year={2020}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n AUTOMATED MACHINE-LEARNING RADIOTHERAPY PLANNING FOR PEDIATRIC AND ADULT BRAIN TUMOURS.\n \n \n \n\n\n \n Tsui, G., Tsang, D., McIntosh, C., Purdie, T., Khandwala, M., Bauman, G., Laperriere, N., Dama, H., & Hodgson, D.\n\n\n \n\n\n\n In RADIOTHERAPY AND ONCOLOGY, volume 150, pages S15–S15, 2020. ELSEVIER IRELAND LTD ELSEVIER HOUSE, BROOKVALE PLAZA, EAST PARK SHANNON, CO …\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
\n 
@inproceedings{tsui2020automated,\n  title={AUTOMATED MACHINE-LEARNING RADIOTHERAPY PLANNING FOR PEDIATRIC AND ADULT BRAIN TUMOURS},\n  author={Tsui, Grace and Tsang, Derek and McIntosh, Chris and Purdie, Tom and Khandwala, Mohammad and Bauman, Glenn and Laperriere, Normand and Dama, Hitesh and Hodgson, David},\n  booktitle={RADIOTHERAPY AND ONCOLOGY},\n  volume={150},\n  pages={S15--S15},\n  year={2020},\n  organization={ELSEVIER IRELAND LTD ELSEVIER HOUSE, BROOKVALE PLAZA, EAST PARK SHANNON, CO~…}\n}
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2019\n \n \n (4)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Method and system for automated quality assurance and automated treatment planning in radiation therapy.\n \n \n \n\n\n \n Purdie, T. G, McIntosh, C. J., & Svistoun, I.\n\n\n \n\n\n\n November 12 2019.\n US Patent 10,475,537\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
\n 
@misc{purdie2019method,\n  title={Method and system for automated quality assurance and automated treatment planning in radiation therapy},\n  author={Purdie, Thomas G and McIntosh, Christopher James and Svistoun, Igor},\n  year={2019},\n  month=nov # "~12",\n  note={US Patent 10,475,537}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Vulnerabilities of radiomic signature development: The need for safeguards.\n \n \n \n\n\n \n Welch, M. L, McIntosh, C., Haibe-Kains, B., Milosevic, M. F, Wee, L., Dekker, A., Huang, S. H., Purdie, T. G, O'Sullivan, B., Aerts, H. J., & others\n\n\n \n\n\n\n Radiotherapy and Oncology, 130: 2–9. 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
\n 
@article{welch2019vulnerabilities,\n  title={Vulnerabilities of radiomic signature development: The need for safeguards},\n  author={Welch, Mattea L and McIntosh, Chris and Haibe-Kains, Benjamin and Milosevic, Michael F and Wee, Leonard and Dekker, Andre and Huang, Shao Hui and Purdie, Thomas G and O'Sullivan, Brian and Aerts, Hugo JWL and others},\n  journal={Radiotherapy and Oncology},\n  volume={130},\n  pages={2--9},\n  year={2019},\n  publisher={Elsevier}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Machine Learning Based Method for Peer Review Rounds Case Prioritization.\n \n \n \n\n\n \n Conroy, L, McIntosh, C, & Purdie, T\n\n\n \n\n\n\n In MEDICAL PHYSICS, volume 46, pages E325–E325, 2019. WILEY 111 RIVER ST, HOBOKEN 07030-5774, NJ 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
\n 
@inproceedings{conroy2019machine,\n  title={Machine Learning Based Method for Peer Review Rounds Case Prioritization},\n  author={Conroy, L and McIntosh, C and Purdie, T},\n  booktitle={MEDICAL PHYSICS},\n  volume={46},\n  number={6},\n  pages={E325--E325},\n  year={2019},\n  organization={WILEY 111 RIVER ST, HOBOKEN 07030-5774, NJ USA}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n 163 Application of Novel Radiotherapy and Imaging Features for Head and Neck Patient Locoregional Failure Predictions.\n \n \n \n\n\n \n Welch, M., McIntosh, C., Wee, L., McNiven, A., Huang, S. H., Zhang, B., Traverso, A., O’Sullivan, B., Hoebers, F., Dekker, A., & others\n\n\n \n\n\n\n Radiotherapy and Oncology, 139: S70. 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
\n 
@article{welch2019163,\n  title={163 Application of Novel Radiotherapy and Imaging Features for Head and Neck Patient Locoregional Failure Predictions},\n  author={Welch, Mattea and McIntosh, Chris and Wee, Leonard and McNiven, Andrea and Huang, Shao Hui and Zhang, Bei-Bei and Traverso, Alberto and O’Sullivan, Brian and Hoebers, Frank and Dekker, Andre and others},\n  journal={Radiotherapy and Oncology},\n  volume={139},\n  pages={S70},\n  year={2019},\n  publisher={Elsevier}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2018\n \n \n (3)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Guided undersampling classification for automated radiation therapy quality assurance of prostate cancer treatment.\n \n \n \n\n\n \n Brown, W E., Sung, K., Aleman, D. M, Moreno-Centeno, E., Purdie, T. G, & McIntosh, C. J\n\n\n \n\n\n\n Medical physics, 45(4): 1306–1316. 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
\n 
@article{brown2018guided,\n  title={Guided undersampling classification for automated radiation therapy quality assurance of prostate cancer treatment},\n  author={Brown, W Eric and Sung, Kisuk and Aleman, Dionne M and Moreno-Centeno, Erick and Purdie, Thomas G and McIntosh, Chris J},\n  journal={Medical physics},\n  volume={45},\n  number={4},\n  pages={1306--1316},\n  year={2018}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Performance Evaluation of An Atlas-Based Machine Learning Approach for Automated Prostate Radiotherapy Planning.\n \n \n \n\n\n \n Conroy, L, McIntosh, C, Berlin, A, Tjong, M, Chung, P, Craig, T, & Purdie, T\n\n\n \n\n\n\n In MEDICAL PHYSICS, volume 45, pages E399–E399, 2018. WILEY 111 RIVER ST, HOBOKEN 07030-5774, NJ 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
\n 
@inproceedings{conroy2018performance,\n  title={Performance Evaluation of An Atlas-Based Machine Learning Approach for Automated Prostate Radiotherapy Planning},\n  author={Conroy, L and McIntosh, C and Berlin, A and Tjong, M and Chung, P and Craig, T and Purdie, T},\n  booktitle={MEDICAL PHYSICS},\n  volume={45},\n  number={6},\n  pages={E399--E399},\n  year={2018},\n  organization={WILEY 111 RIVER ST, HOBOKEN 07030-5774, NJ USA}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Clinical application of a novel voxel-and machine learning-based automated planning method for prostate volumetric arc radiation therapy.\n \n \n \n\n\n \n Berlin, A, Conroy, L, Tjong, M., Craig, T, Chung, P, McIntosh, C, & Purdie, T.\n\n\n \n\n\n\n International Journal of Radiation Oncology, Biology, Physics, 102(3): e533. 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
\n 
@article{berlin2018clinical,\n  title={Clinical application of a novel voxel-and machine learning-based automated planning method for prostate volumetric arc radiation therapy},\n  author={Berlin, A and Conroy, L and Tjong, MC and Craig, T and Chung, P and McIntosh, C and Purdie, TG},\n  journal={International Journal of Radiation Oncology, Biology, Physics},\n  volume={102},\n  number={3},\n  pages={e533},\n  year={2018},\n  publisher={Elsevier}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2017\n \n \n (2)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method.\n \n \n \n\n\n \n McIntosh, C., Welch, M., McNiven, A., Jaffray, D. A, & Purdie, T. G\n\n\n \n\n\n\n Physics in Medicine & Biology, 62(15): 5926. 2017.\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
\n 
@article{mcintosh2017fully,\n  title={Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method},\n  author={McIntosh, Chris and Welch, Mattea and McNiven, Andrea and Jaffray, David A and Purdie, Thomas G},\n  journal={Physics in Medicine \\& Biology},\n  volume={62},\n  number={15},\n  pages={5926},\n  year={2017},\n  publisher={IOP Publishing}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n A Quality control system to automatically detect errors and identify features in radiotherapy treatment plans.\n \n \n \n\n\n \n Balderson, M., McIntosh, C., & Purdie, T.\n\n\n \n\n\n\n In MEDICAL PHYSICS, volume 44, pages 4386–4386, 2017. WILEY 111 RIVER ST, HOBOKEN 07030-5774, NJ 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
\n 
@inproceedings{balderson2017quality,\n  title={A Quality control system to automatically detect errors and identify features in radiotherapy treatment plans},\n  author={Balderson, Michael and McIntosh, Chris and Purdie, Thomas},\n  booktitle={MEDICAL PHYSICS},\n  volume={44},\n  number={8},\n  pages={4386--4386},\n  year={2017},\n  organization={WILEY 111 RIVER ST, HOBOKEN 07030-5774, NJ USA}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2016\n \n \n (3)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Voxel-based dose prediction with multi-patient atlas selection for automated radiotherapy treatment planning.\n \n \n \n\n\n \n McIntosh, C., & Purdie, T. G\n\n\n \n\n\n\n Physics in Medicine & Biology, 62(2): 415. 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
\n 
@article{mcintosh2016voxel,\n  title={Voxel-based dose prediction with multi-patient atlas selection for automated radiotherapy treatment planning},\n  author={McIntosh, Chris and Purdie, Thomas G},\n  journal={Physics in Medicine \\& Biology},\n  volume={62},\n  number={2},\n  pages={415},\n  year={2016},\n  publisher={IOP Publishing}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Automated Quality Assurance at Breast Cancer Rounds—a Process to Improve Efficiency and Quality of Patient Care.\n \n \n \n\n\n \n Rock, K, Barry, A., McIntosh, C, Purdie, T, & Koch, C.\n\n\n \n\n\n\n International Journal of Radiation Oncology, Biology, Physics, 96(2): S232–S233. 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
\n 
@article{rock2016automated,\n  title={Automated Quality Assurance at Breast Cancer Rounds—a Process to Improve Efficiency and Quality of Patient Care},\n  author={Rock, K and Barry, AS and McIntosh, C and Purdie, T and Koch, CA},\n  journal={International Journal of Radiation Oncology, Biology, Physics},\n  volume={96},\n  number={2},\n  pages={S232--S233},\n  year={2016},\n  publisher={Elsevier}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Computing For Medicine: Project 2 Medical Image Analysis.\n \n \n \n\n\n \n McIntosh, C.\n\n\n \n\n\n\n . 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
\n 
@article{mcintosh2016computing,\n  title={Computing For Medicine: Project 2 Medical Image Analysis},\n  author={McIntosh, Chris},\n  year={2016}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2015\n \n \n (2)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Applying a Real Time Pretreatment Review of Radiation Oncology Breast Cancer Rounds: Automated Quality Assurance Results.\n \n \n \n\n\n \n Barry, A., Sole, C., McIntosh, C, Purdie, T., & Koch, C.\n\n\n \n\n\n\n International Journal of Radiation Oncology, Biology, Physics, 93(3): E586. 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
\n 
@article{barry2015applying,\n  title={Applying a Real Time Pretreatment Review of Radiation Oncology Breast Cancer Rounds: Automated Quality Assurance Results},\n  author={Barry, AS and Sole, CV and McIntosh, C and Purdie, TG and Koch, CA},\n  journal={International Journal of Radiation Oncology, Biology, Physics},\n  volume={93},\n  number={3},\n  pages={E586},\n  year={2015},\n  publisher={Elsevier}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Contextual atlas regression forests: multiple-atlas-based automated dose prediction in radiation therapy.\n \n \n \n\n\n \n McIntosh, C., & Purdie, T. G\n\n\n \n\n\n\n IEEE transactions on medical imaging, 35(4): 1000–1012. 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
\n 
@article{mcintosh2015contextual,\n  title={Contextual atlas regression forests: multiple-atlas-based automated dose prediction in radiation therapy},\n  author={McIntosh, Chris and Purdie, Thomas G},\n  journal={IEEE transactions on medical imaging},\n  volume={35},\n  number={4},\n  pages={1000--1012},\n  year={2015},\n  publisher={IEEE}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2014\n \n \n (1)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Novel morphological and appearance features for predicting physical disability from MR images in multiple sclerosis patients.\n \n \n \n\n\n \n Kawahara, J., McIntosh, C., Tam, R., & Hamarneh, G.\n\n\n \n\n\n\n In Computational Methods and Clinical Applications for Spine Imaging: Proceedings of the Workshop held at the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, September 22-26, 2013, Nagoya, Japan, pages 61–73, 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
\n 
@inproceedings{kawahara2014novel,\n  title={Novel morphological and appearance features for predicting physical disability from MR images in multiple sclerosis patients},\n  author={Kawahara, Jeremy and McIntosh, Chris and Tam, Roger and Hamarneh, Ghassan},\n  booktitle={Computational Methods and Clinical Applications for Spine Imaging: Proceedings of the Workshop held at the 16th International Conference on Medical Image Computing and Computer Assisted Intervention, September 22-26, 2013, Nagoya, Japan},\n  pages={61--73},\n  year={2014},\n  organization={Springer International Publishing}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2013\n \n \n (4)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Globally optimal spinal cord segmentation using a minimal path in high dimensions.\n \n \n \n\n\n \n Kawahara, J., McIntosh, C., Tam, R., & Hamarneh, G.\n\n\n \n\n\n\n In 2013 IEEE 10th International Symposium on Biomedical Imaging, pages 848–851, 2013. 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
\n 
@inproceedings{kawahara2013globally,\n  title={Globally optimal spinal cord segmentation using a minimal path in high dimensions},\n  author={Kawahara, Jeremy and McIntosh, Chris and Tam, Roger and Hamarneh, Ghassan},\n  booktitle={2013 IEEE 10th International Symposium on Biomedical Imaging},\n  pages={848--851},\n  year={2013},\n  organization={IEEE}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Groupwise conditional random forests for automatic shape classification and contour quality assessment in radiotherapy planning.\n \n \n \n\n\n \n McIntosh, C., Svistoun, I., & Purdie, T. G\n\n\n \n\n\n\n IEEE transactions on medical imaging, 32(6): 1043–1057. 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
\n 
@article{mcintosh2013groupwise,\n  title={Groupwise conditional random forests for automatic shape classification and contour quality assessment in radiotherapy planning},\n  author={McIntosh, Chris and Svistoun, Igor and Purdie, Thomas G},\n  journal={IEEE transactions on medical imaging},\n  volume={32},\n  number={6},\n  pages={1043--1057},\n  year={2013},\n  publisher={IEEE}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Augmenting auto-context with global geometric features for spinal cord segmentation.\n \n \n \n\n\n \n Kawahara, J., McIntosh, C., Tam, R., & Hamarneh, G.\n\n\n \n\n\n\n In Machine Learning in Medical Imaging: 4th International Workshop, MLMI 2013, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013. Proceedings 4, pages 211–218, 2013. 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
\n 
@inproceedings{kawahara2013augmenting,\n  title={Augmenting auto-context with global geometric features for spinal cord segmentation},\n  author={Kawahara, Jeremy and McIntosh, Chris and Tam, Roger and Hamarneh, Ghassan},\n  booktitle={Machine Learning in Medical Imaging: 4th International Workshop, MLMI 2013, Held in Conjunction with MICCAI 2013, Nagoya, Japan, September 22, 2013. Proceedings 4},\n  pages={211--218},\n  year={2013},\n  organization={Springer International Publishing}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Medical image segmentation: Energy minimization and deformable models.\n \n \n \n\n\n \n McIntosh, C., & Hamarneh, G.\n\n\n \n\n\n\n Medical Imaging: Technology and Applications,619–660. 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
\n 
@article{mcintosh2013medical,\n  title={Medical image segmentation: Energy minimization and deformable models},\n  author={McIntosh, Chris and Hamarneh, Ghassan},\n  journal={Medical Imaging: Technology and Applications},\n  pages={619--660},\n  year={2013}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2011\n \n \n (5)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Perception-based Visualization of Manifold-Valued Medical Images using Distance-Preserving Dimensionality Reduction.\n \n \n \n\n\n \n Hamarneh, G., McIntosh, C., & Drew, M\n\n\n \n\n\n\n Medical Imaging, IEEE Transactions on, (99): 1–1. 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
\n 
@article{hamarneh2011perception,\n  title={Perception-based Visualization of Manifold-Valued Medical Images using Distance-Preserving Dimensionality Reduction},\n  author={Hamarneh, Ghassan and McIntosh, Chris and Drew, M},\n  journal={Medical Imaging, IEEE Transactions on},\n  number={99},\n  pages={1--1},\n  year={2011},\n  publisher={IEEE}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Spinal Cord Segmentation for Volume Estimation in Healthy and Multiple Sclerosis Subjects using Crawlers and Minimal Paths.\n \n \n \n\n\n \n McIntosh, C., Hamarneh, G., Toom, M., & Tam, R. C\n\n\n \n\n\n\n In Healthcare Informatics, Imaging and Systems Biology (HISB), 2011 First IEEE International Conference on, pages 25–31, 2011. 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
\n 
@inproceedings{mcintosh2011spinal,\n  title={Spinal Cord Segmentation for Volume Estimation in Healthy and Multiple Sclerosis Subjects using Crawlers and Minimal Paths},\n  author={McIntosh, Chris and Hamarneh, Ghassan and Toom, Matthew and Tam, Roger C},\n  booktitle={Healthcare Informatics, Imaging and Systems Biology (HISB), 2011 First IEEE International Conference on},\n  pages={25--31},\n  year={2011},\n  organization={IEEE}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Convex Multi-Region Probabilistic Segmentation with Shape Prior in the Isometric Log-Ratio Transformation Space.\n \n \n \n\n\n \n Andrews, S., McIntosh, C., & Hamarneh, G.\n\n\n \n\n\n\n . 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
\n 
@article{andrews2011convex,\n  title={Convex Multi-Region Probabilistic Segmentation with Shape Prior in the Isometric Log-Ratio Transformation Space},\n  author={Andrews, Shawn and McIntosh, Chris and Hamarneh, Ghassan},\n  year={2011}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Medial-based deformable models in nonconvex shape-spaces for medical image segmentation.\n \n \n \n\n\n \n McIntosh, C., & Hamarneh, G.\n\n\n \n\n\n\n IEEE transactions on medical imaging, 31(1): 33–50. 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
\n 
@article{mcintosh2011medial,\n  title={Medial-based deformable models in nonconvex shape-spaces for medical image segmentation},\n  author={McIntosh, Chris and Hamarneh, Ghassan},\n  journal={IEEE transactions on medical imaging},\n  volume={31},\n  number={1},\n  pages={33--50},\n  year={2011},\n  publisher={IEEE}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Energy functionals for medical image segmentation: choices and consequences.\n \n \n \n\n\n \n McIntosh, C.\n\n\n \n\n\n\n . 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
\n 
@article{mcintosh2011energy,\n  title={Energy functionals for medical image segmentation: choices and consequences},\n  author={McIntosh, Christopher},\n  year={2011},\n  publisher={Simon Fraser University}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2009\n \n \n (2)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Optimal weights for convex functionals in medical image segmentation.\n \n \n \n\n\n \n McIntosh, C., & Hamarneh, G.\n\n\n \n\n\n\n Advances in Visual Computing,1079–1088. 2009.\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
\n 
@article{mcintosh2009optimal,\n  title={Optimal weights for convex functionals in medical image segmentation},\n  author={McIntosh, Chris and Hamarneh, Ghassan},\n  journal={Advances in Visual Computing},\n  pages={1079--1088},\n  year={2009},\n  publisher={Springer}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Deformable Organisms: An Artificial Life Framework for Automated Medical Image Analysis.\n \n \n \n\n\n \n Hamarneh, G., McIntosh, C., McInerney, T., & Terzopoulos, D.\n\n\n \n\n\n\n Computational intelligence in medical imaging: techniques and applications,433. 2009.\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
\n 
@article{hamarneh2009deformable,\n  title={Deformable Organisms: An Artificial Life Framework for Automated Medical Image Analysis},\n  author={Hamarneh, Ghassan and McIntosh, Chris and McInerney, Tim and Terzopoulos, Demetri},\n  journal={Computational intelligence in medical imaging: techniques and applications},\n  pages={433},\n  year={2009},\n  publisher={CRC Press}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2007\n \n \n (4)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Is a single energy functional sufficient? Adaptive energy functionals and automatic initialization.\n \n \n \n\n\n \n McIntosh, C., & Hamarneh, G.\n\n\n \n\n\n\n Medical Image Computing and Computer-Assisted Intervention–MICCAI 2007,503–510. 2007.\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
\n 
@article{mcintosh2007single,\n  title={Is a single energy functional sufficient? Adaptive energy functionals and automatic initialization},\n  author={McIntosh, Chris and Hamarneh, Ghassan},\n  journal={Medical Image Computing and Computer-Assisted Intervention--MICCAI 2007},\n  pages={503--510},\n  year={2007},\n  publisher={Springer}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Human limb delineation and joint position recovery using localized boundary models.\n \n \n \n\n\n \n McIntosh, C., Hamarneh, G., & Mori, G.\n\n\n \n\n\n\n In Motion and Video Computing, 2007. WMVC'07. IEEE Workshop on, pages 31–31, 2007. 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
\n 
@inproceedings{mcintosh2007human,\n  title={Human limb delineation and joint position recovery using localized boundary models},\n  author={McIntosh, Chris and Hamarneh, Ghassan and Mori, Greg},\n  booktitle={Motion and Video Computing, 2007. WMVC'07. IEEE Workshop on},\n  pages={31--31},\n  year={2007},\n  organization={IEEE}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Deformable Organisms For Medical Image Analysis.\n \n \n \n\n\n \n Hamarneh, G., & McIntosh, C.\n\n\n \n\n\n\n Deformable Models,387–443. 2007.\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
\n 
@article{hamarneh2007deformable,\n  title={Deformable Organisms For Medical Image Analysis},\n  author={Hamarneh, Ghassan and McIntosh, Chris},\n  journal={Deformable Models},\n  pages={387--443},\n  year={2007},\n  publisher={Springer}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Physically And Statistically Based Deformable Models For Medical Image Analysis.\n \n \n \n\n\n \n Hamarneh, G., & McIntosh, C.\n\n\n \n\n\n\n Deformable Models,335–386. 2007.\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
\n 
@article{hamarneh2007physically,\n  title={Physically And Statistically Based Deformable Models For Medical Image Analysis},\n  author={Hamarneh, Ghassan and McIntosh, Chris},\n  journal={Deformable Models},\n  pages={335--386},\n  year={2007},\n  publisher={Springer}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2006\n \n \n (5)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Vessel crawlers: 3d physically-based deformable organisms for vasculature segmentation and analysis.\n \n \n \n\n\n \n McIntosh, C., & Hamarneh, G.\n\n\n \n\n\n\n In Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on, volume 1, pages 1084–1091, 2006. 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
\n 
@inproceedings{mcintosh2006vessel,\n  title={Vessel crawlers: 3d physically-based deformable organisms for vasculature segmentation and analysis},\n  author={McIntosh, Chris and Hamarneh, Ghassan},\n  booktitle={Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on},\n  volume={1},\n  pages={1084--1091},\n  year={2006},\n  organization={IEEE}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Genetic algorithm driven statistically deformed models for medical image segmentation.\n \n \n \n\n\n \n McIntosh, C., & Hamarneh, G.\n\n\n \n\n\n\n In Genetic and Evolutionary Computation Conference, GECCO, pages 8–12, 2006. \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
\n 
@inproceedings{mcintosh2006genetic,\n  title={Genetic algorithm driven statistically deformed models for medical image segmentation},\n  author={McIntosh, Chris and Hamarneh, Ghassan},\n  booktitle={Genetic and Evolutionary Computation Conference, GECCO},\n  pages={8--12},\n  year={2006}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Spinal crawlers: Deformable organisms for spinal cord segmentation and analysis.\n \n \n \n\n\n \n McIntosh, C., & Hamarneh, G.\n\n\n \n\n\n\n Medical Image Computing and Computer-Assisted Intervention–MICCAI 2006,808–815. 2006.\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
\n 
@article{mcintosh2006spinal,\n  title={Spinal crawlers: Deformable organisms for spinal cord segmentation and analysis},\n  author={McIntosh, Chris and Hamarneh, Ghassan},\n  journal={Medical Image Computing and Computer-Assisted Intervention--MICCAI 2006},\n  pages={808--815},\n  year={2006},\n  publisher={Springer}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n I-DO: A “Deformable Organisms” framework for ITK.\n \n \n \n\n\n \n McIntosh, C., & Hamarneh, G.\n\n\n \n\n\n\n Medical Image Analysis. 2006.\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
\n 
@article{mcintosh2006deformable,\n  title={I-DO: A “Deformable Organisms” framework for ITK},\n  author={McIntosh, Chris and Hamarneh, Ghassan},\n  journal={Medical Image Analysis},\n  year={2006}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Corpus Callosum Segmentation in Magnetic Resonance Images Using Artificial Organisms.\n \n \n \n\n\n \n Hamarneh, G, & McIntosh, C\n\n\n \n\n\n\n . 2006.\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
\n 
@article{hamarneh2006corpus,\n  title={Corpus Callosum Segmentation in Magnetic Resonance Images Using Artificial Organisms},\n  author={Hamarneh, G and McIntosh, C},\n  year={2006}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n 2005\n \n \n (2)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n 3D live-wire-based semi-automatic segmentation of medical images.\n \n \n \n\n\n \n Hamarneh, G., Yang, J., McIntosh, C., & Langille, M.\n\n\n \n\n\n\n In Proceedings of SPIE Medical Imaging: Image Processing, volume 5747, pages 1597–1603, 2005. \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 1 download\n \n \n\n \n \n \n \n \n \n \n\n  \n \n \n\n\n\n
\n 
@inproceedings{hamarneh20053d,\n  title={3D live-wire-based semi-automatic segmentation of medical images},\n  author={Hamarneh, Ghassan and Yang, Johnson and McIntosh, Chris and Langille, Morgan},\n  booktitle={Proceedings of SPIE Medical Imaging: Image Processing},\n  volume={5747},\n  pages={1597--1603},\n  year={2005}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Physics-based deformable organisms for medical image analysis.\n \n \n \n\n\n \n Hamarneh, G., & McIntosh, C.\n\n\n \n\n\n\n In Proc. of SPIE Vol, volume 5747, pages 327, 2005. \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
\n 
@inproceedings{hamarneh2005physics,\n  title={Physics-based deformable organisms for medical image analysis},\n  author={Hamarneh, Ghassan and McIntosh, Chris},\n  booktitle={Proc. of SPIE Vol},\n  volume={5747},\n  pages={327},\n  year={2005}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n
\n
\n  \n undefined\n \n \n (9)\n \n \n
\n
\n \n \n
\n \n\n \n \n \n \n \n Evolutionary Deformable Models for Medical Image Segmentation: A Genetic Algorithm Approach to Optimizing Learned, Intuitive, and Localized Medial-Based Shape Deformation.\n \n \n \n\n\n \n McIntosh, C., & Hamarneh, G.\n\n\n \n\n\n\n In Genetic and Evolutionary Computation, pages 46–67, . Wiley Online Library\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
\n 
@inproceedings{mcintoshevolutionary,\n  title={Evolutionary Deformable Models for Medical Image Segmentation: A Genetic Algorithm Approach to Optimizing Learned, Intuitive, and Localized Medial-Based Shape Deformation},\n  author={McIntosh, Chris and Hamarneh, Ghassan},\n  booktitle={Genetic and Evolutionary Computation},\n  pages={46--67},\n  organization={Wiley Online Library}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Optimal Weights in Convex Functionals: Taking the Guesswork Out of Segmentation.\n \n \n \n\n\n \n McIntosh, C., & Hamarneh, G.\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
\n 
@article{mcintoshoptimal,\n  title={Optimal Weights in Convex Functionals: Taking the Guesswork Out of Segmentation},\n  author={McIntosh, Chris and Hamarneh, Ghassan}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Perception-based Visualization of High-Dimensional Medical Images Using Distance Preserving Dimensionality Reduction.\n \n \n \n\n\n \n Hamarneh, G., McIntosh, C., & Drew, M. S\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
\n 
@article{hamarnehperception,\n  title={Perception-based Visualization of High-Dimensional Medical Images Using Distance Preserving Dimensionality Reduction},\n  author={Hamarneh, Ghassan and McIntosh, Chris and Drew, Mark S}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Radiotherapy and Oncology, 2019, Volume 130, January, pp. 1–196.\n \n \n \n\n\n \n Baumann, M, Bacchus, C, Welch, M., McIntosh, C, Haibe-Kains, B, Milosevic, M., Wee, L, Dekker, A, Huang, S., Purdie, T., & others\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
\n 
@article{baumannradiotherapy,\n  title={Radiotherapy and Oncology, 2019, Volume 130, January, pp. 1--196},\n  author={Baumann, M and Bacchus, C and Welch, ML and McIntosh, C and Haibe-Kains, B and Milosevic, MF and Wee, L and Dekker, A and Huang, SH and Purdie, TG and others}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Noise Isolation in Mixed-Signal Systems Using Alternating Impedance Electromagnetic Bandgap (AI-EBG) Structure-Based Power Distribution Network (PDN)............ J. Choi, V. Govind, M. Swaminathan, and K. Bharath 2 Escape Routing in Modern Area Array Packaging: An Analysis of Need, Trend, and Capability...........................\n \n \n \n\n\n \n Jaiswal, B, Roy, M., Titus, A., Yang, J, Ume, I., Zhang, L, Hsu, L., Wu, W., Chang, E., Zirath, H, & others\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
\n 
@article{jaiswalnoise,\n  title={Noise Isolation in Mixed-Signal Systems Using Alternating Impedance Electromagnetic Bandgap (AI-EBG) Structure-Based Power Distribution Network (PDN)............ J. Choi, V. Govind, M. Swaminathan, and K. Bharath 2 Escape Routing in Modern Area Array Packaging: An Analysis of Need, Trend, and Capability...........................},\n  author={Jaiswal, B and Roy, MK and Titus, AH and Yang, J and Ume, IC and Zhang, L and Hsu, LH and Wu, WC and Chang, EY and Zirath, H and others}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Cardiovascular Signatures of COVID-19 Predict Mortality and Identify Barrier Stabilizing Therapies (preprint).\n \n \n \n\n\n \n Gustafson, D., Ngai, M., Wu, R., Hou, H., Schoffel, A., Erice, C., Mandla, S., Billia, F., Wilson, M., Radisic, M., & others\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
\n 
@article{gustafsoncardiovascular,\n  title={Cardiovascular Signatures of COVID-19 Predict Mortality and Identify Barrier Stabilizing Therapies (preprint)},\n  author={Gustafson, Dakota and Ngai, Michelle and Wu, Ruilin and Hou, Huayun and Schoffel, Alice and Erice, Clara and Mandla, Serena and Billia, Filio and Wilson, Michael and Radisic, Milica and others}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n Barrie Rose Research Day in Palliative Medicine 2022.\n \n \n \n\n\n \n Hanon, B., Liu, A. Z. H., Berlin, A., Haibe-Kains, B., & McIntosh, C.\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
\n 
@article{hanonbarrie,\n  title={Barrie Rose Research Day in Palliative Medicine 2022},\n  author={Hanon, Breffni and Liu, Amy Zhi Hui and Berlin, Alejandro and Haibe-Kains, Benjamin and McIntosh, Christopher}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n 661 Medical Image Segmentation: Energy Minimization and Deformable Models.\n \n \n \n\n\n \n McIntosh, C., & Hamarneh, G.\n\n\n \n\n\n\n Medical Imaging: Technology and Applications,661–692. .\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
\n 
@article{mcintosh661,\n  title={661 Medical Image Segmentation: Energy Minimization and Deformable Models},\n  author={McIntosh, Chris and Hamarneh, Ghassan},\n  journal={Medical Imaging: Technology and Applications},\n  pages={661--692},\n  publisher={CRC Press}\n}\n\n
\n
\n\n\n\n
\n\n\n
\n \n\n \n \n \n \n \n planning Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method.\n \n \n \n\n\n \n Mcintosh, C., Welch, M., Mcniven, A., Jaffray, D. A, & Purdie, T. G\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
\n 
@article{mcintoshplanning,\n  title={planning Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method},\n  author={Mcintosh, Chris and Welch, Mattea and Mcniven, Andrea and Jaffray, David A and Purdie, Thomas G},\n  publisher={IOP Publishing}\n}\n\n
\n
\n\n\n\n
\n\n\n\n\n\n
\n
\n\n\n\n\n
\n\n\n \n\n \n \n \n \n\n
\n"}; document.write(bibbase_data.data);