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Jayashree Kalpathy-Cramer
Publications
- 2023
- [j30]Bin Deng, Hanxue Gu, Hongmin Zhu, Ken Chang, Katharina Viktoria Hoebel, Jay B. Patel, Jayashree Kalpathy-Cramer, Stefan A. Carp:
FDU-Net: Deep Learning-Based Three-Dimensional Diffuse Optical Image Reconstruction. IEEE Trans. Medical Imaging 42(8): 2439-2450 (2023) - [c64]Jay B. Patel, Syed Rakin Ahmed, Ken Chang, Praveer Singh, Mishka Gidwani, Katharina Hoebel, Albert Kim, Christopher P. Bridge, Chung-Jen Teng, Xiaomei Li, Gongwen Xu, Megan McDonald, Ayal Aizer, Wenya Linda Bi, K. Ina Ly, Bruce Rosen, Priscilla K. Brastianos, Raymond Y. Huang, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer:
A Deep Learning Based Framework for Joint Image Registration and Segmentation of Brain Metastases on Magnetic Resonance Imaging. MLHC 2023: 565-587 - 2022
- [c63]Charles Lu, Andréanne Lemay, Ken Chang, Katharina Höbel, Jayashree Kalpathy-Cramer:
Fair Conformal Predictors for Applications in Medical Imaging. AAAI 2022: 12008-12016 - [c62]Sourav Kumar, Anantharaman Lakshminarayanan, Ken Chang, Feri Guretno, Ivan Ho Mien, Jayashree Kalpathy-Cramer, Pavitra Krishnaswamy, Praveer Singh:
Towards More Efficient Data Valuation in Healthcare Federated Learning Using Ensembling. DeCaF/FAIR@MICCAI 2022: 119-129 - [c61]Katharina Hoebel, Christopher P. Bridge, Andréanne Lemay, Ken Chang, Jay B. Patel, Bruce Rosen, Jayashree Kalpathy-Cramer:
Do I know this? segmentation uncertainty under domain shift. Medical Imaging: Image Processing 2022 - [c60]Katharina Hoebel, Christopher P. Bridge, Sara Ahmed, Oluwatosin Akintola, Caroline Chung, Raymond Y. Huang, Jason Johnson, Albert Kim, K. Ina Ly, Ken Chang, Jay B. Patel, Marco Pinho, Tracy Batchelor, Bruce R. Rosen, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer:
Is this good enough? On expert perception of brain tumor segmentation quality. Medical Imaging: Image Perception, Observer Performance, and Technology Assessment 2022 - [i36]Ikbeom Jang, Garrison Danley, Ken Chang, Jayashree Kalpathy-Cramer:
Decreasing Annotation Burden of Pairwise Comparisons with Human-in-the-Loop Sorting: Application in Medical Image Artifact Rating. CoRR abs/2202.04823 (2022) - [i34]Charles Lu, Ken Chang, Praveer Singh, Jayashree Kalpathy-Cramer:
Three Applications of Conformal Prediction for Rating Breast Density in Mammography. CoRR abs/2206.12008 (2022) - [i32]Sourav Kumar, Anantharaman Lakshminarayanan, Ken Chang, Feri Guretno, Ivan Ho Mien, Jayashree Kalpathy-Cramer, Pavitra Krishnaswamy, Praveer Singh:
Towards More Efficient Data Valuation in Healthcare Federated Learning using Ensembling. CoRR abs/2209.05424 (2022) - 2021
- [j26]Andrew Beers, James M. Brown, Ken Chang, Katharina Hoebel, Jay B. Patel, K. Ina Ly, Sara M. Tolaney, Priscilla K. Brastianos, Bruce R. Rosen, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer:
DeepNeuro: an open-source deep learning toolbox for neuroimaging. Neuroinformatics 19(1): 127-140 (2021) - [c59]Jay B. Patel, Ken Chang, Syed Rakin Ahmed, Ikbeom Jang, Jayashree Kalpathy-Cramer:
Opportunities and Challenges for Deep Learning in Brain Lesions. BrainLes@MICCAI (1) 2021: 25-36 - [i30]Sharut Gupta, Praveer Singh, Ken Chang, Liangqiong Qu, Mehak Aggarwal, Nishanth Thumbavanam Arun, Ashwin Vaswani, Shruti Raghavan, Vibha Agarwal, Mishka Gidwani, Katharina Hoebel, Jay B. Patel, Charles Lu, Christopher P. Bridge, Daniel L. Rubin, Jayashree Kalpathy-Cramer:
Addressing catastrophic forgetting for medical domain expansion. CoRR abs/2103.13511 (2021) - [i25]Charles Lu, Andréanne Lemay, Ken Chang, Katharina Hoebel, Jayashree Kalpathy-Cramer:
Fair Conformal Predictors for Applications in Medical Imaging. CoRR abs/2109.04392 (2021) - [i24]Charles Lu, Ken Chang, Praveer Singh, Stuart R. Pomerantz, Sean Doyle, Sujay Kakarmath, Christopher P. Bridge, Jayashree Kalpathy-Cramer:
Deploying clinical machine learning? Consider the following... CoRR abs/2109.06919 (2021) - [i20]Raghav Mehta, Angelos Filos, Ujjwal Baid, Chiharu Sako, Richard McKinley, Michael Rebsamen, Katrin Dätwyler, Raphael Meier, Piotr Radojewski, Gowtham Krishnan Murugesan, Sahil S. Nalawade, Chandan Ganesh, Benjamin C. Wagner, Fang F. Yu, Baowei Fei, Ananth J. Madhuranthakam, Joseph A. Maldjian, Laura Alexandra Daza, Catalina Gómez Caballero, Pablo Arbeláez, Chengliang Dai, Shuo Wang, Hadrien Raynaud, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai, Subhashis Banerjee, Linmin Pei, Murat Ak, Sarahi Rosas-González, Ilyess Zemmoura, Clovis Tauber, Minh H. Vu, Tufve Nyholm, Tommy Löfstedt, Laura Mora Ballestar, Verónica Vilaplana, Hugh McHugh, Gonzalo D. Maso Talou, Alan Wang, Jay B. Patel, Ken Chang, Katharina Hoebel, Mishka Gidwani, Nishanth Thumbavanam Arun, Sharut Gupta, Mehak Aggarwal, Praveer Singh, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer, Nicolas Boutry, Alexis Huard, Lasitha Vidyaratne, Md Monibor Rahman, Khan M. Iftekharuddin, Joseph Chazalon, Élodie Puybareau, Guillaume Tochon, Jun Ma, Mariano Cabezas, Xavier Lladó, Arnau Oliver, Liliana Valencia, Sergi Valverde, Mehdi Amian, Mohammadreza Soltaninejad, Andriy Myronenko, Ali Hatamizadeh, Xue Feng, Quan Dou, Nicholas J. Tustison, Craig H. Meyer, Nisarg A. Shah, Sanjay N. Talbar, Marc-André Weber, Abhishek Mahajan, András Jakab, Roland Wiest, Hassan M. Fathallah-Shaykh, Arash Nazeri, Mikhail Milchenko, Daniel S. Marcus, Aikaterini Kotrotsou, Rivka Colen, John B. Freymann, Justin S. Kirby, Christos Davatzikos, Bjoern H. Menze, Spyridon Bakas, Yarin Gal, Tal Arbel:
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results. CoRR abs/2112.10074 (2021) - 2020
- [j24]Niranjan Balachandar, Ken Chang, Jayashree Kalpathy-Cramer, Daniel L. Rubin:
Accounting for data variability in multi-institutional distributed deep learning for medical imaging. J. Am. Medical Informatics Assoc. 27(5): 700-708 (2020) - [j23]Niranjan Balachandar, Ken Chang, Jayashree Kalpathy-Cramer, Daniel L. Rubin:
Corrigendum to: Accounting for data variability in multi-institutional distributed deep learning for medical imaging. J. Am. Medical Informatics Assoc. 27(8): 1340 (2020) - [j22]Matthew D. Li, Ken Chang, Ben Bearce, Connie Y. Chang, Ambrose J. Huang, J. Peter Campbell, James M. Brown, Praveer Singh, Katharina Viktoria Hoebel, Deniz Erdogmus, Stratis Ioannidis, William E. Palmer, Michael F. Chiang, Jayashree Kalpathy-Cramer:
Siamese neural networks for continuous disease severity evaluation and change detection in medical imaging. npj Digit. Medicine 3 (2020) - [c55]Jay B. Patel, Ken Chang, Katharina Hoebel, Mishka Gidwani, Nishanth Thumbavanam Arun, Sharut Gupta, Mehak Aggarwal, Praveer Singh, Bruce R. Rosen, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer:
Segmentation, Survival Prediction, and Uncertainty Estimation of Gliomas from Multimodal 3D MRI Using Selective Kernel Networks. BrainLes@MICCAI (2) 2020: 228-240 - [c54]Holger R. Roth, Ken Chang, Praveer Singh, Nir Neumark, Wenqi Li, Vikash Gupta, Sharut Gupta, Liangqiong Qu, Alvin Ihsani, Bernardo C. Bizzo, Yuhong Wen, Varun Buch, Meesam Shah, Felipe Kitamura, Matheus Mendonça, Vitor Lavor, Ahmed Harouni, Colin Compas, Jesse Tetreault, Prerna Dogra, Yan Cheng, Selnur Erdal, Richard D. White, Behrooz Hashemian, Thomas J. Schultz, Miao Zhang, Adam McCarthy, B. Min Yun, Elshaimaa Sharaf, Katharina Viktoria Hoebel, Jay B. Patel, Bryan Chen, Sean Ko, Evan Leibovitz, Etta D. Pisano, Laura Coombs, Daguang Xu, Keith J. Dreyer, Ittai Dayan, Ram C. Naidu, Mona Flores, Daniel L. Rubin, Jayashree Kalpathy-Cramer:
Federated Learning for Breast Density Classification: A Real-World Implementation. DART/DCL@MICCAI 2020: 181-191 - [c53]Jay B. Patel, Mishka Gidwani, Ken Chang, Jayashree Kalpathy-Cramer:
Radiomics and Radiogenomics with Deep Learning in Neuro-oncology. MLCN/RNO-AI@MICCAI 2020: 199-211 - [c52]Katharina Hoebel, Vincent Andrearczyk, Andrew Beers, Jay B. Patel, Ken Chang, Adrien Depeursinge, Henning Müller, Jayashree Kalpathy-Cramer:
An exploration of uncertainty information for segmentation quality assessment. Medical Imaging: Image Processing 2020: 113131K - [i19]Nishanth Thumbavanam Arun, Nathan Gaw, Praveer Singh, Ken Chang, Katharina Viktoria Hoebel, Jay B. Patel, Mishka Gidwani, Jayashree Kalpathy-Cramer:
Assessing the validity of saliency maps for abnormality localization in medical imaging. CoRR abs/2006.00063 (2020) - [i18]Nishanth Thumbavanam Arun, Nathan Gaw, Praveer Singh, Ken Chang, Mehak Aggarwal, Bryan Chen, Katharina Hoebel, Sharut Gupta, Jay B. Patel, Mishka Gidwani, Julius Adebayo, Matthew D. Li, Jayashree Kalpathy-Cramer:
Assessing the (Un)Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging. CoRR abs/2008.02766 (2020) - [i17]Holger R. Roth, Ken Chang, Praveer Singh, Nir Neumark, Wenqi Li, Vikash Gupta, Sharut Gupta, Liangqiong Qu, Alvin Ihsani, Bernardo C. Bizzo, Yuhong Wen, Varun Buch, Meesam Shah, Felipe Kitamura, Matheus Mendonça, Vitor Lavor, Ahmed Harouni, Colin Compas, Jesse Tetreault, Prerna Dogra, Yan Cheng, Selnur Erdal, Richard D. White, Behrooz Hashemian, Thomas J. Schultz, Miao Zhang, Adam McCarthy, B. Min Yun, Elshaimaa Sharaf, Katharina Viktoria Hoebel, Jay B. Patel, Bryan Chen, Sean Ko, Evan Leibovitz, Etta D. Pisano, Laura Coombs, Daguang Xu, Keith J. Dreyer, Ittai Dayan, Ram C. Naidu, Mona Flores, Daniel L. Rubin, Jayashree Kalpathy-Cramer:
Federated Learning for Breast Density Classification: A Real-World Implementation. CoRR abs/2009.01871 (2020) - [i16]Mehak Aggarwal, Nishanth Thumbavanam Arun, Sharut Gupta, Ashwin Vaswani, Bryan Chen, Matthew D. Li, Ken Chang, Jay B. Patel, Katherine Höbel, Mishka Gidwani, Jayashree Kalpathy-Cramer, Praveer Singh:
Towards Trainable Saliency Maps in Medical Imaging. CoRR abs/2011.07482 (2020) - [i15]Sharut Gupta, Praveer Singh, Ken Chang, Mehak Aggarwal, Nishanth Thumbavanam Arun, Liangqiong Qu, Katharina Hoebel, Jay B. Patel, Mishka Gidwani, Ashwin Vaswani, Daniel L. Rubin, Jayashree Kalpathy-Cramer:
The unreasonable effectiveness of Batch-Norm statistics in addressing catastrophic forgetting across medical institutions. CoRR abs/2011.08096 (2020) - 2019
- [i12]Vivek Sharma, Praneeth Vepakomma, Tristan Swedish, Ken Chang, Jayashree Kalpathy-Cramer, Ramesh Raskar:
ExpertMatcher: Automating ML Model Selection for Users in Resource Constrained Countries. CoRR abs/1910.02312 (2019) - [i11]Vivek Sharma, Praneeth Vepakomma, Tristan Swedish, Ken Chang, Jayashree Kalpathy-Cramer, Ramesh Raskar:
ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations. CoRR abs/1910.03731 (2019) - [i10]Katharina Hoebel, Ken Chang, Jay B. Patel, Praveer Singh, Jayashree Kalpathy-Cramer:
Give me (un)certainty - An exploration of parameters that affect segmentation uncertainty. CoRR abs/1911.06357 (2019) - [i9]Maarten G. Poirot, Praneeth Vepakomma, Ken Chang, Jayashree Kalpathy-Cramer, Rajiv Gupta, Ramesh Raskar:
Split Learning for collaborative deep learning in healthcare. CoRR abs/1912.12115 (2019) - 2018
- [j20]Ken Chang, Niranjan Balachandar, Carson K. Lam, Darvin Yi, James M. Brown, Andrew Beers, Bruce R. Rosen, Daniel L. Rubin, Jayashree Kalpathy-Cramer:
Distributed deep learning networks among institutions for medical imaging. J. Am. Medical Informatics Assoc. 25(8): 945-954 (2018) - [c44]Andrew Beers, Ken Chang, James M. Brown, Elizabeth R. Gerstner, Bruce R. Rosen, Jayashree Kalpathy-Cramer:
Sequential neural networks for biologically-informed glioma segmentation. Medical Imaging: Image Processing 2018: 1057433 - [i8]Andrew Beers, James M. Brown, Ken Chang, J. Peter Campbell, Susan Ostmo, Michael F. Chiang, Jayashree Kalpathy-Cramer:
High-resolution medical image synthesis using progressively grown generative adversarial networks. CoRR abs/1805.03144 (2018) - [i7]Andrew Beers, James M. Brown, Ken Chang, Katharina Hoebel, Elizabeth R. Gerstner, Bruce R. Rosen, Jayashree Kalpathy-Cramer:
DeepNeuro: an open-source deep learning toolbox for neuroimaging. CoRR abs/1808.04589 (2018) - [i6]Szu-Yeu Hu, Andrew Beers, Ken Chang, Kathi Höbel, J. Peter Campbell, Deniz Erdogmus, Stratis Ioannidis, Jennifer G. Dy, Michael F. Chiang, Jayashree Kalpathy-Cramer, James M. Brown:
Deep feature transfer between localization and segmentation tasks. CoRR abs/1811.02539 (2018) - [i5]Bruno Lecouat, Ken Chang, Chuan-Sheng Foo, Balagopal Unnikrishnan, James M. Brown, Houssam Zenati, Andrew Beers, Vijay Chandrasekhar, Jayashree Kalpathy-Cramer, Pavitra Krishnaswamy:
Semi-Supervised Deep Learning for Abnormality Classification in Retinal Images. CoRR abs/1812.07832 (2018) - 2017
- [i3]Andrew Beers, Ken Chang, James M. Brown, Emmett Sartor, C. P. Mammen, Elizabeth R. Gerstner, Bruce R. Rosen, Jayashree Kalpathy-Cramer:
Sequential 3D U-Nets for Biologically-Informed Brain Tumor Segmentation. CoRR abs/1709.02967 (2017) - [i2]Ken Chang, Niranjan Balachandar, Carson K. Lam, Darvin Yi, James M. Brown, Andrew Beers, Bruce R. Rosen, Daniel L. Rubin, Jayashree Kalpathy-Cramer:
Institutionally Distributed Deep Learning Networks. CoRR abs/1709.05929 (2017)
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