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2020 – today
- 2024
[j32]Kendall Schmidt
, Benjamin Bearce, Ken Chang, Laura Coombs, Keyvan Farahani, Marawan Elbatel, Kaouther Mouheb, Robert Marti, Ruipeng Zhang, Ya Zhang, Yanfeng Wang, Yaojun Hu, Haochao Ying, Yuyang Xu, Conrad Testagrose, Mutlu Demirer, Vikash Gupta, Ünal Akünal, Markus Bujotzek, Klaus H. Maier-Hein, Yi Qin, Xiaomeng Li, Jayashree Kalpathy-Cramer, Holger R. Roth:
Fair evaluation of federated learning algorithms for automated breast density classification: The results of the 2022 ACR-NCI-NVIDIA federated learning challenge. Medical Image Anal. 95: 103206 (2024)- [j31]Sarthak Pati, Sourav Kumar, Amokh Varma, Brandon Edwards, Charles Lu, Liangqiong Qu, Justin J. Wang, Anantharaman Lakshminarayanan, Shih-han Wang, Micah J. Sheller, Ken Chang, Praveer Singh, Daniel L. Rubin, Jayashree Kalpathy-Cramer, Spyridon Bakas:
Privacy preservation for federated learning in health care. Patterns 5(7): 100974 (2024) - [i41]Tiago Gonçalves, Dagoberto Pulido-Arias, Julian Willett, Katharina Viktoria Hoebel, Mason C. Cleveland, Syed Rakin Ahmed, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer, Jaime S. Cardoso, Christopher P. Bridge, Albert E. Kim:
Deep Learning-based Prediction of Breast Cancer Tumor and Immune Phenotypes from Histopathology. CoRR abs/2404.16397 (2024) - [i40]Kendall Schmidt, Ben Bearce, Ken Chang, Laura Coombs, Keyvan Farahani, Marawan Elbatel, Kaouther Mouheb, Robert Marti, Ruipeng Zhang, Yao Zhang, Yanfeng Wang, Yaojun Hu, Haochao Ying, Yuyang Xu, Conrad Testagrose, Mutlu Demirer, Vikash Gupta, Ünal Akünal, Markus Bujotzek, Klaus H. Maier-Hein, Yi Qin, Xiaomeng Li, Jayashree Kalpathy-Cramer, Holger R. Roth:
Fair Evaluation of Federated Learning Algorithms for Automated Breast Density Classification: The Results of the 2022 ACR-NCI-NVIDIA Federated Learning Challenge. CoRR abs/2405.14900 (2024) - 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) - [c65]Mena Shenouda, Aditi Kaveti, Isabella Flerlage, Jayashree Kalpathy-Cramer, Maryellen L. Giger, Samuel G. Armato III:
Assessing robustness of a deep-learning model for COVID-19 classification on chest radiographs. Medical Imaging: Computer-Aided Diagnosis 2023 - [c64]Jay B. Patel, Syed Rakin Ahmed, Ken Chang, Praveer Singh, Mishka Gidwani, Katharina Hoebel, Albert E. 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 - [i39]Katharina Viktoria Hoebel, Andréanne Lemay, John Peter Campbell, Susan Ostmo, Michael F. Chiang, Christopher P. Bridge, Matthew D. Li, Praveer Singh, Aaron S. Coyner, Jayashree Kalpathy-Cramer:
A generalized framework to predict continuous scores from medical ordinal labels. CoRR abs/2305.19097 (2023) - [i38]Guillermo Lorenzo, Syed Rakin Ahmed, David A. Hormuth II, Brenna Vaughn, Jayashree Kalpathy-Cramer, Luis Solorio, Thomas E. Yankeelov, Héctor Gómez:
Patient-specific, mechanistic models of tumor growth incorporating artificial intelligence and big data. CoRR abs/2308.14925 (2023) - [i37]Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah, Alejandro F. Frangi, Alena Buyx, Anais Emelie, Andrea Lara, Antonio R. Porras, An-Wen Chan, Arcadi Navarro, Ben Glocker, Benard Ohene Botwe, Bishesh Khanal, Brigit Beger, Carol C. Wu, Celia Cintas, Curtis P. Langlotz, Daniel Rueckert, Deogratias Mzurikwao, Dimitrios I. Fotiadis, Doszhan Zhussupov, Enzo Ferrante, Erik Meijering, Eva Weicken, Fabio A. González, Folkert W. Asselbergs, Fred W. Prior, Gabriel P. Krestin, Gary S. Collins, Geletaw Sahle Tegenaw, Georgios Kaissis, Gianluca Misuraca, Gianna Tsakou, Girish Dwivedi, Haridimos Kondylakis, Harsha Jayakody, Henry C. Woodruff, Hugo J. W. L. Aerts, Ian Walsh, Ioanna Chouvarda, Irène Buvat, Islem Rekik, James S. Duncan, Jayashree Kalpathy-Cramer, Jihad Zahir, Jinah Park, John Mongan, Judy W. Gichoya, Julia A. Schnabel, et al.:
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare. CoRR abs/2309.12325 (2023) - 2022
- [j29]Christopher P. Bridge, Chris Gorman, Steven D. Pieper, Sean W. Doyle, Jochen K. Lennerz, Jayashree Kalpathy-Cramer, David A. Clunie, Andriy Fedorov, Markus D. Herrmann:
Highdicom: a Python Library for Standardized Encoding of Image Annotations and Machine Learning Model Outputs in Pathology and Radiology. J. Digit. Imaging 35(6): 1719-1737 (2022) - [j28]Andréanne Lemay, Katharina Hoebel, Christopher P. Bridge, Brian Befano, Silvia De Sanjosé, Didem Egemen, Ana Cecilia Rodriguez, Mark Schiffman, John Peter Campbell, Jayashree Kalpathy-Cramer:
Improving the repeatability of deep learning models with Monte Carlo dropout. npj Digit. Medicine 5 (2022) - [j27]Miao Zhang, Liangqiong Qu, Praveer Singh, Jayashree Kalpathy-Cramer, Daniel L. Rubin:
SplitAVG: A Heterogeneity-Aware Federated Deep Learning Method for Medical Imaging. IEEE J. Biomed. Health Informatics 26(9): 4635-4644 (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 E. 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) - [i35]Andréanne Lemay, Katharina Hoebel, Christopher P. Bridge, Brian Befano, Silvia De Sanjosé, Didem Egemen, Ana Cecilia Rodriguez, Mark Schiffman, John Peter Campbell, Jayashree Kalpathy-Cramer:
Improving the repeatability of deep learning models with Monte Carlo dropout. CoRR abs/2202.07562 (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) - [i33]Charles Lu, Syed Rakin Ahmed, Praveer Singh, Jayashree Kalpathy-Cramer:
Estimating Test Performance for AI Medical Devices under Distribution Shift with Conformal Prediction. CoRR abs/2207.05796 (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) - [i31]M. Jorge Cardoso, Wenqi Li, Richard Brown, Nic Ma, Eric Kerfoot, Yiheng Wang, Benjamin Murray, Andriy Myronenko, Can Zhao, Dong Yang, Vishwesh Nath, Yufan He, Ziyue Xu, Ali Hatamizadeh, Wentao Zhu, Yun Liu, Mingxin Zheng, Yucheng Tang, Isaac Yang, Michael Zephyr, Behrooz Hashemian, Sachidanand Alle, Mohammad Zalbagi Darestani, Charlie Budd, Marc Modat, Tom Vercauteren, Guotai Wang, Yiwen Li, Yipeng Hu, Yunguan Fu, Benjamin Gorman, Hans J. Johnson, Brad W. Genereaux, Barbaros S. Erdal, Vikash Gupta, Andres Diaz-Pinto, Andre Dourson, Lena Maier-Hein, Paul F. Jaeger, Michael Baumgartner, Jayashree Kalpathy-Cramer, Mona Flores, Justin S. Kirby, Lee A. D. Cooper, Holger R. Roth, Daguang Xu, David Bericat, Ralf Floca, S. Kevin Zhou, Haris Shuaib, Keyvan Farahani, Klaus H. Maier-Hein, Stephen R. Aylward, Prerna Dogra, Sébastien Ourselin, Andrew Feng:
MONAI: An open-source framework for deep learning in healthcare. CoRR abs/2211.02701 (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) - [j25]Yoganand Balagurunathan, Andrew Beers, Michael F. McNitt-Gray, Lubomir M. Hadjiiski, Sandy Napel, Dmitry B. Goldgof, Gustavo Pérez, Pablo Arbeláez, Alireza Mehrtash, Tina Kapur, Ehwa Yang, Jung Won Moon, Gabriel Bernardino Perez, Ricard Delgado-Gonzalo, Mohammad Mehdi Farhangi, Amir A. Amini, Renkun Ni, Xue Feng, Aditya Bagari, Kiran Vaidhya, Benjamin Veasey, Wiem Safta, Hichem Frigui, Joseph Enguehard, Ali Gholipour, Laura Silvana Castillo, Laura Alexandra Daza, Paul F. Pinsky, Jayashree Kalpathy-Cramer, Keyvan Farahani:
Lung Nodule Malignancy Prediction in Sequential CT Scans: Summary of ISBI 2018 Challenge. IEEE Trans. Medical Imaging 40(12): 3748-3761 (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 - [c58]Veysi Yildiz, Stratis Ioannidis, Ilkay Yildiz, Peng Tian, John Peter Campbell, Susan Ostmo, Jayashree Kalpathy-Cramer, Michael F. Chiang, Deniz Erdogmus, Jennifer G. Dy:
Structural Visual Guidance Attention Networks In Retinopathy Of Prematurity. ISBI 2021: 353-357 - [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) - [i29]Christopher P. Bridge, Chris Gorman, Steven D. Pieper, Sean W. Doyle, Jochen K. Lennerz, Jayashree Kalpathy-Cramer, David A. Clunie, Andriy Fedorov, Markus D. Herrmann:
Highdicom: A Python library for standardized encoding of image annotations and machine learning model outputs in pathology and radiology. CoRR abs/2106.07806 (2021) - [i28]Ujjwal Baid, Satyam Ghodasara, Michel Bilello, Suyash Mohan, Evan Calabrese, Errol Colak, Keyvan Farahani, Jayashree Kalpathy-Cramer, Felipe C. Kitamura, Sarthak Pati, Luciano M. Prevedello, Jeffrey D. Rudie, Chiharu Sako, Russell T. Shinohara, Timothy Bergquist, Rong Chai, James A. Eddy, Julia Elliott, Walter Reade, Thomas Schaffter, Thomas Yu, Jiaxin Zheng, BraTS Annotators, Christos Davatzikos, John Mongan, Christopher Hess, Soonmee Cha, Javier E. Villanueva-Meyer, John B. Freymann, Justin S. Kirby, Benedikt Wiestler, Priscila Crivellaro, Rivka R. Colen, Aikaterini Kotrotsou, Daniel S. Marcus, Mikhail Milchenko, Arash Nazeri, Hassan M. Fathallah-Shaykh, Roland Wiest, András Jakab, Marc-André Weber, Abhishek Mahajan, Bjoern H. Menze, Adam E. Flanders, Spyridon Bakas:
The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification. CoRR abs/2107.02314 (2021) - [i27]Miao Zhang, Liangqiong Qu, Praveer Singh, Jayashree Kalpathy-Cramer, Daniel L. Rubin:
SplitAVG: A heterogeneity-aware federated deep learning method for medical imaging. CoRR abs/2107.02375 (2021) - [i26]Charles Lu, Andréanne Lemay, Katharina Hoebel, Jayashree Kalpathy-Cramer:
Evaluating subgroup disparity using epistemic uncertainty in mammography. CoRR abs/2107.02716 (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) - [i23]Aaron S. Coyner, Praveer Singh, James M. Brown, Susan Ostmo, R. V. Paul Chan, Michael F. Chiang, Jayashree Kalpathy-Cramer, J. Peter Campbell:
Not Color Blind: AI Predicts Racial Identity from Black and White Retinal Vessel Segmentations. CoRR abs/2109.13845 (2021) - [i22]Charles Lu, Jayashree Kalpathy-Cramer:
Distribution-Free Federated Learning with Conformal Predictions. CoRR abs/2110.07661 (2021) - [i21]Andréanne Lemay, Katharina Hoebel, Christopher P. Bridge, Didem Egemen, Ana Cecilia Rodriguez, Mark Schiffman, John Peter Campbell, Jayashree Kalpathy-Cramer:
Monte Carlo dropout increases model repeatability. CoRR abs/2111.06754 (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) - [c57]Ilkay Yildiz, Jennifer G. Dy, Deniz Erdogmus, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Stratis Ioannidis:
Fast and Accurate Ranking Regression. AISTATS 2020: 77-88 - [c56]Aaron S. Coyner, Jimmy Chen, John Peter Campbell, Susan Ostmo, Praveer Singh, Jayashree Kalpathy-Cramer, Michael F. Chiang:
Diagnosability of Synthetic Retinal Fundus Images for Plus Disease Detection in Retinopathy of Prematurity. AMIA 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)
2010 – 2019
- 2019
- [j21]Ilkay Yildiz, Peng Tian, Jennifer G. Dy, Deniz Erdogmus, James M. Brown, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Stratis Ioannidis:
Classification and comparison via neural networks. Neural Networks 118: 65-80 (2019) - [c51]Yuan Guo, Jennifer G. Dy, Deniz Erdogmus, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Stratis Ioannidis:
Variational Inference from Ranked Samples with Features. ACML 2019: 599-614 - [c50]Peng Tian, Yuan Guo, Jayashree Kalpathy-Cramer, Susan Ostmo, John Peter Campbell, Michael F. Chiang, Jennifer G. Dy, Deniz Erdogmus, Stratis Ioannidis:
A Severity Score for Retinopathy of Prematurity. KDD 2019: 1809-1819 - [c49]Mara Graziani, James M. Brown, Vincent Andrearczyk, Veysi Yildiz, J. Peter Campbell, Deniz Erdogmus, Stratis Ioannidis, Michael F. Chiang, Jayashree Kalpathy-Cramer, Henning Müller:
Improved interpretability for computer-aided severity assessment of retinopathy of prematurity. Medical Imaging: Computer-Aided Diagnosis 2019: 109501R - [c48]Khalil Ouardini, Huijuan Yang, Balagopal Unnikrishnan, Manon Romain, Camille Garcin, Houssam Zenati, J. Peter Campbell, Michael F. Chiang, Jayashree Kalpathy-Cramer, Vijay Chandrasekhar, Pavitra Krishnaswamy, Chuan-Sheng Foo:
Towards Practical Unsupervised Anomaly Detection on Retinal Images. DART/MIL3ID@MICCAI 2019: 225-234 - [c47]Yuan Guo, Jennifer G. Dy, Deniz Erdogmus, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Stratis Ioannidis:
Accelerated Experimental Design for Pairwise Comparisons. SDM 2019: 432-440 - [p4]Henning Müller, Jayashree Kalpathy-Cramer, Alba García Seco de Herrera:
Experiences from the ImageCLEF Medical Retrieval and Annotation Tasks. Information Retrieval Evaluation in a Changing World 2019: 231-250 - [i14]Yuan Guo, Jennifer G. Dy, Deniz Erdogmus, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Stratis Ioannidis:
Accelerated Experimental Design for Pairwise Comparisons. CoRR abs/1901.06080 (2019) - [i13]Jin Chao, Ahmad Al Badawi, Balagopal Unnikrishnan, Jie Lin, Chan Fook Mun, James M. Brown, J. Peter Campbell, Michael F. Chiang, Jayashree Kalpathy-Cramer, Vijay Ramaseshan Chandrasekhar, Pavitra Krishnaswamy, Khin Mi Mi Aung:
CaRENets: Compact and Resource-Efficient CNN for Homomorphic Inference on Encrypted Medical Images. CoRR abs/1901.10074 (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) - [j19]Frank Hopfgartner, Allan Hanbury, Henning Müller, Ivan Eggel, Krisztian Balog, Torben Brodt, Gordon V. Cormack, Jimmy Lin, Jayashree Kalpathy-Cramer, Noriko Kando, Makoto P. Kato, Anastasia Krithara, Tim Gollub, Martin Potthast, Evelyne Viegas, Simon Mercer:
Evaluation-as-a-Service for the Computational Sciences: Overview and Outlook. ACM J. Data Inf. Qual. 10(4): 15:1-15:32 (2018) - [j18]Yangming Ou, Lilla Zöllei, Xiao Da, Kallirroi Retzepi, Shawn N. Murphy, Elizabeth R. Gerstner, Bruce R. Rosen, Patricia Ellen Grant, Jayashree Kalpathy-Cramer, Randy L. Gollub:
Field of View Normalization in Multi-Site Brain MRI. Neuroinformatics 16(3-4): 431-444 (2018) - [c46]Aaron S. Coyner, Ryan Swan, James M. Brown, Jayashree Kalpathy-Cramer, Sang-Jin Kim, John Peter Campbell, Karyn Jonas, Susan Ostmo, R. V. P. Chan, Michael F. Chiang:
Deep Learning for Image Quality Assessment of Fundus Images in Retinopathy of Prematurity. AMIA 2018 - [c45]Yuan Guo, Peng Tian, Jayashree Kalpathy-Cramer, Susan Ostmo, J. Peter Campbell, Michael F. Chiang, Deniz Erdogmus, Jennifer G. Dy, Stratis Ioannidis:
Experimental Design under the Bradley-Terry Model. IJCAI 2018: 2198-2204 - [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
- [j17]Matthieu Lê, Hervé Delingette, Jayashree Kalpathy-Cramer, Elizabeth R. Gerstner, Tracy Batchelor, Jan Unkelbach, Nicholas Ayache:
Personalized Radiotherapy Planning Based on a Computational Tumor Growth Model. IEEE Trans. Medical Imaging 36(3): 815-825 (2017) - [c43]Aaron S. Coyner, Ryan Swan, Jayashree Kalpathy-Cramer, Sang-Jin Kim, John Peter Campbell, Karyn Jonas, Susan Ostmo, R. V. P. Chan, Michael F. Chiang:
Automated Image Quality Assessment for Fundus Images in Retinopathy of Prematurity. AMIA 2017 - [i4]Cagdas Ulas, Christine Preibisch, Jonathan Sperl, Thomas Pyka, Jayashree Kalpathy-Cramer, Bjoern Holger Menze:
Accelerated Reconstruction of Perfusion-Weighted MRI Enforcing Jointly Local and Nonlocal Spatio-temporal Constraints. CoRR abs/1708.07808 (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) - 2016
- [j16]Jayashree Kalpathy-Cramer, Binsheng Zhao, Dmitry B. Goldgof, Yuhua Gu, Xingwei Wang, Hao Yang, Yongqiang Tan, Robert J. Gillies, Sandy Napel:
A Comparison of Lung Nodule Segmentation Algorithms: Methods and Results from a Multi-institutional Study. J. Digit. Imaging 29(4): 476-487 (2016) - [j15]Henning Müller, Jayashree Kalpathy-Cramer, Allan Hanbury, Keyvan Farahani, Rinat Sergeev, Jin H. Paik, Arno Klein, Antonio Criminisi, Andrew D. Trister, Thea Norman, David N. Kennedy, Ganapati Srinivasa, Artem Mamonov, Nina Preuss:
Report on the Cloud-Based Evaluation Approaches Workshop 2015. SIGIR Forum 50(1): 38-41 (2016) - [j14]Matthieu Lê, Hervé Delingette, Jayashree Kalpathy-Cramer, Elizabeth R. Gerstner, Tracy Batchelor, Jan Unkelbach, Nicholas Ayache:
MRI Based Bayesian Personalization of a Tumor Growth Model. IEEE Trans. Medical Imaging 35(10): 2329-2339 (2016) - [c42]Lee A. D. Cooper, Jayashree Kalpathy-Cramer, William Hsu, Ashish Sharma:
Quantitative Imaging and Imaging Informatics in the Era of Precision Medicine. AMIA 2016 - [c41]Peng Tian, Esra Ataer Cansizoglu, Jayashree Kalpathy-Cramer, Susan Ostmo, Karyn Jonas, R. V. P. Chan, J. Peter Campbell, Michael F. Chiang, Deniz Erdogmus:
Toward a severity index for ROP: An unsupervised approach. EMBC 2016: 1312-1315 - 2015
- [j13]Dina Demner-Fushman, Sameer K. Antani, Jayashree Kalpathy-Cramer, Henning Müller:
A decade of community-wide efforts in advancing medical image understanding and retrieval. Comput. Medical Imaging Graph. 39: 1-2 (2015) - [j12]Jayashree Kalpathy-Cramer, Alba Garcia Seco de Herrera, Dina Demner-Fushman, Sameer K. Antani, Steven Bedrick, Henning Müller:
Evaluating performance of biomedical image retrieval systems - An overview of the medical image retrieval task at ImageCLEF 2004-2013. Comput. Medical Imaging Graph. 39: 55-61 (2015) - [j11]Verónica Bolón-Canedo, Esra Ataer Cansizoglu, Deniz Erdogmus, Jayashree Kalpathy-Cramer, Oscar Fontenla-Romero, Amparo Alonso-Betanzos, Michael F. Chiang:
Dealing with inter-expert variability in retinopathy of prematurity: A machine learning approach. Comput. Methods Programs Biomed. 122(1): 1-15 (2015) - [j10]Frank Hopfgartner, Allan Hanbury, Henning Müller, Noriko Kando, Simon Mercer, Jayashree Kalpathy-Cramer, Martin Potthast, Tim Gollub, Anastasia Krithara, Jimmy Lin, Krisztian Balog, Ivan Eggel:
Report on the Evaluation-as-a-Service (EaaS) Expert Workshop. SIGIR Forum 49(1): 57-65 (2015) - [j9]Bjoern H. Menze, András Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Keyvan Farahani, Justin S. Kirby, Yuliya Burren, Nicole Porz, Johannes Slotboom, Roland Wiest, Levente Lanczi, Elizabeth R. Gerstner, Marc-André Weber, Tal Arbel, Brian B. Avants, Nicholas Ayache, Patricia Buendia, D. Louis Collins, Nicolas Cordier, Jason J. Corso, Antonio Criminisi, Tilak Das, Herve Delingette, Çagatay Demiralp, Christopher R. Durst, Michel Dojat, Senan Doyle, Joana Festa, Florence Forbes, Ezequiel Geremia, Ben Glocker, Polina Golland, Xiaotao Guo, Andac Hamamci, Khan M. Iftekharuddin, Raj Jena, Nigel M. John, Ender Konukoglu, Danial Lashkari, José Antonio Mariz, Raphael Meier, Sérgio Pereira, Doina Precup, Stephen J. Price, Tammy Riklin Raviv, Syed M. S. Reza, Michael T. Ryan, Duygu Sarikaya, Lawrence H. Schwartz, Hoo-Chang Shin, Jamie Shotton, Carlos A. Silva, Nuno J. Sousa, Nagesh K. Subbanna, Gábor Székely, Thomas J. Taylor, Owen M. Thomas, Nicholas J. Tustison, Gözde B. Ünal, Flor Vasseur, Max Wintermark, Dong Hye Ye, Liang Zhao, Binsheng Zhao, Darko Zikic, Marcel Prastawa, Mauricio Reyes, Koen Van Leemput:
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS). IEEE Trans. Medical Imaging 34(10): 1993-2024 (2015) - [c40]Kourosh Jafari-Khouzani, Elizabeth R. Gerstner, Bruce R. Rosen, Jayashree Kalpathy-Cramer:
Upsampling dynamic contrast enhanced MRI. ISBI 2015: 1032-1035 - [c39]Verónica Bolón-Canedo, Esra Ataer Cansizoglu, Deniz Erdogmus, Jayashree Kalpathy-Cramer, Michael F. Chiang:
A GMM-based feature extraction technique for the automated diagnosis of Retinopathy of Prematurity. ISBI 2015: 1498-1501 - [c38]Esra Ataer Cansizoglu, Yuichi Taguchi, Jayashree Kalpathy-Cramer, Michael F. Chiang, Deniz Erdogmus:
Analysis of shape assumptions in 3D reconstruction of retina from multiple fundus images. ISBI 2015: 1502-1505 - [c37]Matthieu Lê, Hervé Delingette, Jayashree Kalpathy-Cramer, Elizabeth R. Gerstner, Tracy Batchelor, Jan Unkelbach, Nicholas Ayache:
Bayesian Personalization of Brain Tumor Growth Model. MICCAI (2) 2015: 424-432 - [i1]Allan Hanbury, Henning Müller, Krisztian Balog, Torben Brodt, Gordon V. Cormack, Ivan Eggel, Tim Gollub, Frank Hopfgartner, Jayashree Kalpathy-Cramer, Noriko Kando, Anastasia Krithara, Jimmy Lin, Simon Mercer, Martin Potthast:
Evaluation-as-a-Service: Overview and Outlook. CoRR abs/1512.07454 (2015) - 2014
- [j8]Bekir Dizdaroglu, Esra Ataer Cansizoglu, Jayashree Kalpathy-Cramer, Katie Keck, Michael F. Chiang, Deniz Erdogmus:
Structure-based level set method for automatic retinal vasculature segmentation. EURASIP J. Image Video Process. 2014: 39 (2014) - [j7]David A. Gutman, William D. Dunn, Jake Cobb, Richard Martin Stoner, Jayashree Kalpathy-Cramer, Bradley J. Erickson:
Web based tools for visualizing imaging data and development of XNATView, a zero footprint image viewer. Frontiers Neuroinformatics 8: 53 (2014) - [j6]Jayashree Kalpathy-Cramer, Musaddiq Awan,