Jayashree Kalpathy-Cramer

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 84

Top Venues

CoRR

IEEE Trans. Medical Imaging

ISBI

AMIA

Publications

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) (2024)
Kendall Schmidt, Ben Bearce, Ken Chang, Laura Coombs, Keyvan Farahani, Marawan Elbatel, Kaouther Mouhebe, 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 (2024)
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 (2024)
Kendall Schmidt, Benjamin Bearce, Ken Chang, Laura Coombs, Keyvan Farahani, Marawan Elbatel, Kaouther Mouhebe, 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 (2024)
Jay B. Patel, Syed Rakin Ahmed, Ken Chang, Praveer Singh, Mishka Gidwani, Katharina Hoebel, Albert Kim, Christopher Bridge, Chung-Jen Teng, Xiaomei Li, Gongwen Xu, Megan McDonald, Ayal Aizer, Wenya Linda Bi, Ina Ly, Bruce R. Rosen, Priscilla 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)
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 (2023)
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) (2023)
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 (2023)
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 (2023)
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)
Charles Lu, Ken Chang, Praveer Singh, Jayashree Kalpathy-Cramer
Three Applications of Conformal Prediction for Rating Breast Density in Mammography. CoRR (2022)
Sourav Kumar, A. 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)
Charles Lu, Andréanne Lemay, Ken Chang, Katharina Höbel, Jayashree Kalpathy-Cramer
Fair Conformal Predictors for Applications in Medical Imaging. AAAI (2022)
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)
Sourav Kumar, A. 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 (2022)
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 (2022)
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) (2022)
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, Sebastien Ourselin, Andrew Feng
MONAI: An open-source framework for deep learning in healthcare. CoRR (2022)
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)
Charles Lu, Syed Rakin Ahmed, Praveer Singh, Jayashree Kalpathy-Cramer
Estimating Test Performance for AI Medical Devices under Distribution Shift with Conformal Prediction. CoRR (2022)
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)
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) (2022)
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 (2022)
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 (2021)
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 (2021)
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 (2021)
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 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 (2021)
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) (2021)
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 (2021)
Charles Lu, Andréanne Lemay, Ken Chang, Katharina Hoebel, Jayashree Kalpathy-Cramer
Fair Conformal Predictors for Applications in Medical Imaging. CoRR (2021)
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 (2021)
Charles Lu, Andréanne Lemay, Katharina Hoebel, Jayashree Kalpathy-Cramer
Evaluating subgroup disparity using epistemic uncertainty in mammography. CoRR (2021)
Miao Zhang, Liangqiong Qu, Praveer Singh, Jayashree Kalpathy-Cramer, Daniel L. Rubin
SplitAVG: A heterogeneity-aware federated deep learning method for medical imaging. CoRR (2021)
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)
Charles Lu, Jayashree Kalpathy-Cramer
Distribution-Free Federated Learning with Conformal Predictions. CoRR (2021)
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)
Yoganand Balagurunathan, Andrew Beers, Michael F. McNitt-Gray, Lubomir M. Hadjiiski, Sandy Napel, Dmitry B. Goldgof, Gustavo Pérez, Pablo Arbelaez, 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) (2021)
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, 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 Meyer, Nisarg A. Shah, Sanjay 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 (2021)
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)
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 (2020)
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) (2020)
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 (2020)
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 (2020)
Jay B. Patel, Mishka Gidwani, Ken Chang, Jayashree Kalpathy-Cramer
Radiomics and Radiogenomics with Deep Learning in Neuro-oncology. MLCN/RNO-AI@MICCAI (2020)
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)
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 (2020)
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) (2020)
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 (2020)
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)
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)
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)
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)
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 (2019)
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 (2019)
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)
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)
Maarten G. Poirot, Praneeth Vepakomma, Ken Chang, Jayashree Kalpathy-Cramer, Rajiv Gupta, Ramesh Raskar
Split Learning for collaborative deep learning in healthcare. CoRR (2019)
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)
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 (2019)
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 (2019)
Vivek Sharma, Praneeth Vepakomma, Tristan Swedish, Ken Chang, Jayashree Kalpathy-Cramer, Ramesh Raskar
ExpertMatcher: Automating ML Model Selection for Clients using Hidden Representations. CoRR (2019)
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)
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 (2019)
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)
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) (2018)
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) (2018)
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 (2018)
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 (2018)
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) (2018)
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 (2018)
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)
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)
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)
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 (2018)
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)
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 (2017)
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) (2017)
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 (2017)
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 (2017)
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) (2016)
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)
Lee A. D. Cooper, Jayashree Kalpathy-Cramer, William Hsu, Ashish Sharma
Quantitative Imaging and Imaging Informatics in the Era of Precision Medicine. AMIA (2016)
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) (2016)
Henning Müller, Jayashree Kalpathy-Cramer, Allan Hanbury, Keyvan Farahani, Rinat Sergeev, Jin H. Paik, Arno Klein, Antonio Criminisi, Andrew 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) (2016)
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 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) (2015)
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)
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 (2015)
Kourosh Jafari-Khouzani, Elizabeth R. Gerstner, Bruce R. Rosen, Jayashree Kalpathy-Cramer
Upsampling dynamic contrast enhanced MRI. ISBI (2015)
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)
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 (2015)
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)
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 (2015)
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) (2015)
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) (2015)
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 (2014)
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 (2014)
Jayashree Kalpathy-Cramer, Musaddiq Awan, Steven Bedrick, Coen R. N. Rasch, David I. Rosenthal, Clifton D. Fuller
Development of a Software for Quantitative Evaluation Radiotherapy Target and Organ-at-Risk Segmentation Comparison. J. Digit. Imaging 27 (1) (2014)
Alba Garcia Seco de Herrera, Jayashree Kalpathy-Cramer, Dina Demner-Fushman, Sameer K. Antani, Henning Müller
Overview of the ImageCLEF 2013 Medical Tasks. CLEF (Working Notes) (2013)
Esra Ataer Cansizoglu, Erhan Bas, Jayashree Kalpathy-Cramer, Gregory C. Sharp, Deniz Erdogmus
Contour-based shape representation using principal curves. Pattern Recognit. 46 (4) (2013)
Vanina Taliercio, Judith R. Logan, Jayashree Kalpathy-Cramer, Paula Otero
Developing a Survey to Assess Factors that Contribute to Physician Involvement in Clinical Research. MedInfo (2013)

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Jayashree Kalpathy-Cramer