Give me (un)certainty - An exploration of parameters that affect segmentation uncertainty. - Katharina Hoebel; Ken Chang; Jay B. Patel; Praveer Singh; Jayashree Kalpathy-Cramer (CoRR, 2019)

Segmentation, Survival Prediction, and Uncertainty Estimation of Gliomas from Multimodal 3D MRI Using Selective Kernel Networks. - 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 (BrainLes@MICCAI (2), 2020)

Radiomics and Radiogenomics with Deep Learning in Neuro-oncology. - Jay B. Patel; Mishka Gidwani; Ken Chang; Jayashree Kalpathy-Cramer (MLCN/RNO-AI@MICCAI, 2020)

Federated Learning for Breast Density Classification: A Real-World Implementation. - Holger R. Roth; Ken Chang; Praveer Singh; Nir Neumark; Wenqi Li 001; Vikash Gupta; Sharut Gupta; Liangqiong Qu; Alvin Ihsani; Bernardo C. Bizzo; Yuhong Wen; Varun Buch; et al. (DART/DCL@MICCAI, 2020)

An exploration of uncertainty information for segmentation quality assessment. - Katharina Hoebel; Vincent Andrearczyk; Andrew Beers; Jay B. Patel; Ken Chang; Adrien Depeursinge; Henning Müller; Jayashree Kalpathy-Cramer (Image Processing, 2020)

Assessing the validity of saliency maps for abnormality localization in medical imaging. - Nishanth Thumbavanam Arun; Nathan Gaw; Praveer Singh; Ken Chang; Katharina Viktoria Hoebel; Jay B. Patel; Mishka Gidwani; Jayashree Kalpathy-Cramer (CoRR, 2020)

Assessing the (Un)Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging. - 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; et al. (CoRR, 2020)

Towards Trainable Saliency Maps in Medical Imaging. - 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 (CoRR, 2020)

The unreasonable effectiveness of Batch-Norm statistics in addressing catastrophic forgetting across medical institutions. - 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 (CoRR, 2020)

A framework to analyze decision strategies for multi-band spectrum sensing in cognitive radios. - Jay B. Patel; Steven D. Collins; Birsen Sirkeci-Mergen (Phys. Commun., 2020)

Opportunities and Challenges for Deep Learning in Brain Lesions. - Jay B. Patel; Ken Chang; Syed Rakin Ahmed; Ikbeom Jang; Jayashree Kalpathy-Cramer (BrainLes@MICCAI (1), 2021)

Addressing catastrophic forgetting for medical domain expansion. - 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; et al. (CoRR, 2021)

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results. - 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; et al. (CoRR, 2021)

DeepNeuro: an open-source deep learning toolbox for neuroimaging. - Andrew Beers; James M. Brown 001; 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 (Neuroinformatics, 2021)

Do I know this? segmentation uncertainty under domain shift. - Katharina Hoebel; Christopher P. Bridge; Andréanne Lemay; Ken Chang; Jay B. Patel; Bruce Rosen 001; Jayashree Kalpathy-Cramer (Image Processing, 2022)

Is this good enough? On expert perception of brain tumor segmentation quality. - 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; et al. (Image Perception, Observer Performance, and Technology Assessment, 2022)

A Deep Learning Based Framework for Joint Image Registration and Segmentation of Brain Metastases on Magnetic Resonance Imaging. - 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; et al. (MLHC, 2023)

FDU-Net: Deep Learning-Based Three-Dimensional Diffuse Optical Image Reconstruction. - Bin Deng; Hanxue Gu; Hongmin Zhu; Ken Chang; Katharina Viktoria Hoebel; Jay B. Patel; Jayashree Kalpathy-Cramer; Stefan A. Carp (IEEE Trans. Medical Imaging, 2023)

Multimodal Deep Learning-Based Prediction of Immune Checkpoint Inhibitor Efficacy in Brain Metastases. - Tobias R. Bodenmann; Nelson Gil; Felix J. Dorfner; Mason C. Cleveland; Jay B. Patel; Shreyas Bhat Brahmavar; Melisa S. Guelen; Dagoberto Pulido-Arias; Jayashree Kalpathy-Cramer; Jean-Philippe Thiran; Bruce R. Rosen; Elizabeth R. Gerstner; et al. (CaPTion@MICCAI, 2024)

Addressing Catastrophic Forgetting by Modulating Global Batch Normalization Statistics for Medical Domain Expansion. - Sharut Gupta; Ken Chang; Liangqiong Qu; Aakanksha Rana; Syed Rakin Ahmed; Mehak Aggarwal; Nishanth Thumbavanam Arun; Ashwin Vaswani; Shruti Raghavan; Vibha Agarwal; Mishka Gidwani; Katharina Hoebel; et al. (AIPAD/PILM@MICCAI, 2024)

Cycle-GANs Generated Difference Maps to Interpret Race Prediction from Medical Images. - Lakshika Rathi; Giacomo Nebbia; Ken Chang; Sourav Kumar; Aarushi Gupta; Syed Rakin Ahmed; Jay B. Patel; Christopher Clark; Yoga Advaith Veturi; Aaron S. Coyner; Aakanksha Rana; Christopher P. Bridge; et al. (FAIMI/EPIMI@MICCAI, 2024)

Towards Early Detection: AI-Based Five-Year Forecasting of Breast Cancer Risk Using Digital Breast Tomosynthesis Imaging. - Manon A. Dorster; Felix J. Dorfner; Mason C. Cleveland; Melisa S. Guelen; Jay B. Patel; Dania Daye; Jean-Philippe Thiran; Albert E. Kim; Christopher P. Bridge (Deep-Breath@MICCAI, 2025)