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  2023 (6)
CohortFinder: An open-source tool for data-driven partitioning of biomedical image cohorts to yield robust machine learning models. Fan, F.; Martinez, G.; Desilvio, T.; Shin, J.; Chen, Y.; Wang, B.; Ozeki, T.; Lafarge, M.; Koelzer, V.; Barisoni, L.; Madabhushi, A.; Viswanath, S.; and Janowczyk, A. 2023.
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Deep learning of renal scans in children with antenatal hydronephrosis. Weaver, J.; Logan, J.; Broms, R.; Antony, M.; Rickard, M.; Erdman, L.; Edwins, R.; Pominville, R.; Hannick, J.; Woo, L.; Viteri, B.; D'Souza, N.; Viswanath, S.; Flask, C.; Lorenzo, A.; Fan, Y.; and Tasian, G. Journal of Pediatric Urology, 19(5). 2023.
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Integrating Radiomics with Clinicoradiological Scoring Can Predict High-Risk Patients Who Need Surgery in Crohn’s Disease: A Pilot Study. Chirra, P.; Sharma, A.; Bera, K.; Cohn, H.; Kurowski, J.; Amann, K.; Rivero, M.; Madabhushi, A.; Lu, C.; Paspulati, R.; Stein, S.; Katz, J.; Viswanath, S.; and Dave, M. Inflammatory Bowel Diseases, 29(3). 2023.
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Mesenchymal stem cells ameliorate inflammation in an experimental model of Crohn's disease via the mesentery. Dave, M.; Dev, A.; Somoza, R.; Zhao, N.; Viswanath, S.; Mina, P.; Chirra, P.; Obmann, V.; Mahabeleshwar, G.; Menghini, P.; Johnson, B.; Nolta, J.; Soto, C.; Osme, A.; Khuat, L.; Murphy, W.; Caplan, A.; and Cominelli, F. 2023.
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Region-specific deep learning models for accurate segmentation of rectal structures on post-chemoradiation T2w MRI: a multi-institutional, multi-reader study. DeSilvio, T.; Antunes, J.; Bera, K.; Chirra, P.; Le, H.; Liska, D.; Stein, S.; Marderstein, E.; Hall, W.; Paspulati, R.; Gollamudi, J.; Purysko, A.; and Viswanath, S. Frontiers in Medicine, 10. 2023.
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Integrating Multi-Plane and Multi-Region Radiomic Features to Predict Pathologic Response to Neoadjuvant Chemoradiation in Rectal Cancers via Pre-Treatment MRI. DeSilvio, T.; Bao, L.; Seth, D.; Chirra, P.; Singh, S.; Sridharan, A.; Labbad, M.; Bingmer, K.; Jodeh, D.; Marderstein, E.; Paspulati, R.; Liska, D.; Friedman, K.; Krishnamurthi, S.; Stein, S.; Purysko, A.; and Viswanath, S. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE, volume 12466, 2023.
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  2022 (8)
Crohn's disease related strictures in cross-sectional imaging: More than meets the eye?. Sleiman, J.; Chirra, P.; Gandhi, N.; Baker, M.; Lu, C.; Gordon, I.; Viswanath, S.; and Rieder, F. United European Gastroenterology Journal, 10(10). 2022.
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Staging and Restaging of Rectal Cancer with MRI: A Pictorial Review. Wetzel, A.; Viswanath, S.; Gorgun, E.; Ozgur, I.; Allende, D.; Liska, D.; and Purysko, A. Seminars in Ultrasound, CT and MRI, 43(6). 2022.
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Editorial for “Selecting Candidates for Organ-Preserving Strategies After Neoadjuvant Chemoradiotherapy for Rectal Cancer: Development and Validation of a Model Integrating MRI Radiomics and Pathomics”. Viswanath, S. Journal of Magnetic Resonance Imaging, 56(4). 2022.
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RADIomic Spatial TexturAl Descriptor (RADISTAT): Quantifying Spatial Organization of Imaging Heterogeneity Associated With Tumor Response to Treatment. Antunes, J.; Ismail, M.; Hossain, I.; Wang, Z.; Prasanna, P.; Madabhushi, A.; Tiwari, P.; and Viswanath, S. IEEE Journal of Biomedical and Health Informatics, 26(6). 2022.
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Challenges in ensuring the generalizability of image quantitation methods for MRI. Keenan, K.; Delfino, J.; Jordanova, K.; Poorman, M.; Chirra, P.; Chaudhari, A.; Baessler, B.; Winfield, J.; Viswanath, S.; and deSouza, N. Medical Physics, 49(4). 2022.
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Residual Wavelon Convolutional Networks for Characterization of Disease Response on MRI. Sadri, A.; DeSilvio, T.; Chirra, P.; Singh, S.; and Viswanath, S. Volume 13433 LNCS 2022.
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Deep hybrid convolutional wavelet networks: Application to predicting response to chemoradiation in rectal cancers via MRI. Sadri, A.; Desilvio, T.; Chirra, P.; Purysko, A.; Paspulati, R.; Friedman, K.; Krishnamurthi, S.; Liska, D.; Stein, S.; and Viswanath, S. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE, volume 12033, 2022.
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Identifying radiomic features associated with disease activity, patient outcomes, and serum phenotypes in pediatric Crohn's disease via MRI. Chirra, P.; Muchhala, A.; Amann, K.; Krishnan, K.; Kurowski, J.; and Viswanath, S. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE, volume 12034, 2022.
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  2021 (4)
Correlation between image quality metrics of magnetic resonance images and the neural network segmentation accuracy. Muthusivarajan, R.; Celaya, A.; Yung, J.; Viswanath, S.; Marcus, D.; Chung, C.; and Fuentes, D. 2021.
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Prospective Evaluation of Repeatability and Robustness of Radiomic Descriptors in Healthy Brain Tissue Regions In Vivo Across Systematic Variations in T2-Weighted Magnetic Resonance Imaging Acquisition Parameters. Eck, B.; Chirra, P.; Muchhala, A.; Hall, S.; Bera, K.; Tiwari, P.; Madabhushi, A.; Seiberlich, N.; and Viswanath, S. Journal of Magnetic Resonance Imaging, 54(3). 2021.
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Adipokine Resistin Levels at Time of Pediatric Crohn Disease Diagnosis Predict Escalation to Biologic Therapy. Kurowski, J.; Achkar, J.; Gupta, R.; Barbur, I.; Bonfield, T.; Worley, S.; Remer, E.; Fiocchi, C.; Viswanath, S.; and Kay, M. Inflammatory Bowel Diseases, 27(7). 2021.
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SPARTA: An Integrated Stability, Discriminability, and Sparsity Based Radiomic Feature Selection Approach. Sadri, A.; Azarianpour Esfahani, S.; Chirra, P.; Antunes, J.; Pattiam Giriprakash, P.; Leo, P.; Madabhushi, A.; and Viswanath, S. Volume 12903 LNCS 2021.
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  2020 (10)
Identifying cross-scale associations between radiomic and pathomic signatures of non-small cell lung cancer subtypes: Preliminary results. Alvarez-Jimenez, C.; Sandino, A.; Prasanna, P.; Gupta, A.; Viswanath, S.; and Romero, E. Cancers, 12(12). 2020.
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Technical Note: MRQy — An open-source tool for quality control of MR imaging data. Sadri, A.; Janowczyk, A.; Zhou, R.; Verma, R.; Beig, N.; Antunes, J.; Madabhushi, A.; Tiwari, P.; and Viswanath, S. Medical Physics, 47(12). 2020.
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Radiomic Features of Primary Rectal Cancers on Baseline T2-Weighted MRI Are Associated With Pathologic Complete Response to Neoadjuvant Chemoradiation: A Multisite Study. Antunes, J.; Ofshteyn, A.; Bera, K.; Wang, E.; Brady, J.; Willis, J.; Friedman, K.; Marderstein, E.; Kalady, M.; Stein, S.; Purysko, A.; Paspulati, R.; Gollamudi, J.; Madabhushi, A.; and Viswanath, S. Journal of Magnetic Resonance Imaging, 52(5). 2020.
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Radiomic texture and shape descriptors of the rectal environment on post-chemoradiation T2-weighted MRI are associated with pathologic tumor stage regression in rectal cancers: A retrospective, multi-institution study. Alvarez-Jimenez, C.; Antunes, J.; Talasila, N.; Bera, K.; Brady, J.; Gollamudi, J.; Marderstein, E.; Kalady, M.; Purysko, A.; Willis, J.; Stein, S.; Friedman, K.; Paspulati, R.; Delaney, C.; Romero, E.; Madabhushi, A.; and Viswanath, S. Cancers, 12(8). 2020.
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MRQy: An open-source tool for quality control of MR imaging data. Sadri, A.; Janowczyk, A.; Zhou, R.; Verma, R.; Beig, N.; Antunes, J.; Madabhushi, A.; Tiwari, P.; and Viswanath, S. 2020.
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Quality assessment of brain MRI scans using a dense neural network model and image metrics. Gupta, A.; Sadri, A.; Viswanath, S.; and Tiwari, P. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE, volume 11312, 2020.
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Texture kinetic features from pre-treatment DCE MRI for predicting pathologic tumor stage regression after neoadjuvant chemoradiation in rectal cancers. Nanda, S.; Antunes, J.; Bera, K.; Brady, J.; Friedman, K.; Willis, J.; Paspulati, R.; and Viswanath, S. In Proceedings of SPIE - The International Society for Optical Engineering, volume 11315, 2020.
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Multi-site evaluation of stable radiomic features for more accurate evaluation of pathologic downstaging on MRI after chemoradiation for rectal cancers. Selvam, A.; Antunes, J.; Bera, K.; Ofshteyn, A.; Brady, J.; Bingmer, K.; Friedman, K.; Stein, S.; Paspulati, R.; Purysko, A.; Kalady, M.; Madabhushi, A.; and Viswanath, S. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE, volume 11314, 2020.
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Cell density features from histopathological images to differentiate non-small cell lung cancer subtypes. Sandino, A.; Alvarez-Jimenez, C.; Mosquera-Zamudio, A.; Viswanath, S.; and Romero, E. In Proceedings of SPIE - The International Society for Optical Engineering, volume 11330, 2020.
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Sparse Wavelet Networks. Sadri, A.; Celebi, M.; Rahnavard, N.; and Viswanath, S. IEEE Signal Processing Letters, 27. 2020.
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  2019 (8)
Differentiating Cancerous and Non-cancerous Prostate Tissue Using Multi-scale Texture Analysis on MRI. Alvarez-Jimenez, C.; Barrera, C.; Munera, N.; Viswanath, S.; and Romero, E. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2019.
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Multisite evaluation of radiomic feature reproducibility and discriminability for identifying peripheral zone prostate tumors on MRI. Chirra, P.; Leo, P.; Yim, M.; Bloch, B.; Rastinehad, A.; Purysko, A.; Rosen, M.; Madabhushi, A.; and Viswanath, S. Journal of Medical Imaging, 6(2). 2019.
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Comparing radiomic classifiers and classifier ensembles for detection of peripheral zone prostate tumors on T2-weighted MRI: A multi-site study. Viswanath, S.; Chirra, P.; Yim, M.; Rofsky, N.; Purysko, A.; Rosen, M.; Bloch, B.; and Madabhushi, A. BMC Medical Imaging, 19(1). 2019.
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Radiomics in genitourinary cancers: Prostate cancer. Viswanath, S.; and Madabhushi, A. 2019.
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Structural rectal atlas deformation (stRAD) features for characterizing intra- and peri-wall chemoradiation response on MRI. Antunes, J.; Wei, Z.; Alvarez-Jimenez, C.; Romero, E.; Ismail, M.; Madabhushi, A.; Tiwari, P.; and Viswanath, S. Volume 11767 LNCS 2019.
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Region-specific fully convolutional networks for segmentation of the rectal wall on post-chemoradiation T2w MRI. Desilvio, T.; Antunes, J.; Chirra, P.; Bera, K.; Gollamudi, J.; Paspulati, R.; Delaney, C.; and Viswanath, S. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE, volume 10951, 2019.
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Radiomic characterization of perirectal fat on MRI enables accurate assessment of tumor regression and lymph node metastasis in rectal cancers after chemoradiation. Yim, M.; Wei, Z.; Antunes, J.; Sehgal, N.; Bera, K.; Brady, J.; Friedman, K.; Willis, J.; Purysko, A.; Paspulati, R.; Madabhushi, A.; and Viswanath, S. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE, volume 10951, 2019.
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Integrating radiomic features from T2-weighted and contrast-enhanced MRI to evaluate pathologic rectal tumor regression after chemoradiation. Nanda, S.; Antunes, J.; Selvam, A.; Bera, K.; Brady, J.; Gollamudi, J.; Friedman, K.; Willis, J.; Delaney, C.; Paspulati, R.; Madabhushi, A.; and Viswanath, S. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE, volume 10951, 2019.
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  2018 (6)
Radiomic features on MRI enable risk categorization of prostate cancer patients on active surveillance: Preliminary findings. Algohary, A.; Viswanath, S.; Shiradkar, R.; Ghose, S.; Pahwa, S.; Moses, D.; Jambor, I.; Shnier, R.; Böhm, M.; Haynes, A.; Brenner, P.; Delprado, W.; Thompson, J.; Pulbrock, M.; Purysko, A.; Verma, S.; Ponsky, L.; Stricker, P.; and Madabhushi, A. Journal of Magnetic Resonance Imaging, 48(3). 2018.
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Identifying the morphologic basis for radiomic features in distinguishing different Gleason grades of prostate cancer on MRI: Preliminary findings. Penzias, G.; Singanamalli, A.; Elliott, R.; Gollamudi, J.; Shih, N.; Feldman, M.; Stricker, P.; Delprado, W.; Tiwari, S.; Böhm, M.; Haynes, A.; Ponsky, L.; Fu, P.; Tiwari, P.; Viswanath, S.; and Madabhushi, A. PLoS ONE, 13(8). 2018.
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Coregistration of Preoperative MRI with Ex Vivo Mesorectal Pathology Specimens to Spatially Map Post-treatment Changes in Rectal Cancer Onto In Vivo Imaging: Preliminary Findings. Antunes, J.; Viswanath, S.; Brady, J.; Crawshaw, B.; Ros, P.; Steele, S.; Delaney, C.; Paspulati, R.; Willis, J.; and Madabhushi, A. Academic Radiology, 25(7). 2018.
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A review of machine learning in obesity. DeGregory, K.; Kuiper, P.; DeSilvio, T.; Pleuss, J.; Miller, R.; Roginski, J.; Fisher, C.; Harness, D.; Viswanath, S.; Heymsfield, S.; Dungan, I.; and Thomas, D. Obesity Reviews, 19(5). 2018.
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Automated segmentation and radiomic characterization of visceral fat on bowel MRIs for Crohn's disease. Barbur, I.; Kurowski, J.; Bera, K.; Thawani, R.; Achkar, J.; Fiocchi, C.; Kay, M.; Gupta, R.; and Viswanath, S. In Progress in Biomedical Optics and Imaging - Proceedings of SPIE, volume 10576, 2018.
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