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ORCID2nd DART / 1st DCL @ MICCAI 2020: Lima, Peru
- Shadi Albarqouni
, Spyridon Bakas, Konstantinos Kamnitsas, M. Jorge Cardoso, Bennett A. Landman, Wenqi Li, Fausto Milletari, Nicola Rieke, Holger Roth, Daguang Xu, Ziyue Xu:
Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning - Second MICCAI Workshop, DART 2020, and First MICCAI Workshop, DCL 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4-8, 2020, Proceedings. Lecture Notes in Computer Science 12444, Springer 2020, ISBN 978-3-030-60547-6
DART 2020
- Yaxin Chen, Benteng Ma, Yong Xia:
α-UNet++: A Data-Driven Neural Network Architecture for Medical Image Segmentation. 3-12 - Zichun Huang, Hongyan Mao, Ningkang Jiang, Xiaoling Wang:
DAPR-Net: Domain Adaptive Predicting-Refinement Network for Retinal Vessel Segmentation. 13-22 - Zisheng Li, Masahiro Ogino:
Augmented Radiology: Patient-Wise Feature Transfer Model for Glioma Grading. 23-30 - Hao Guan, Erkun Yang, Pew-Thian Yap, Dinggang Shen, Mingxia Liu:
Attention-Guided Deep Domain Adaptation for Brain Dementia Identification with Multi-site Neuroimaging Data. 31-40 - James Tong, Dwarikanath Mahapatra, C. Paul Bonnington, Tom Drummond, Zongyuan Ge:
Registration of Histopathology Images Using Self Supervised Fine Grained Feature Maps. 41-51 - Junlin Yang, Xiaoxiao Li, Daniel H. Pak, Nicha C. Dvornek, Julius Chapiro, Ming De Lin, James S. Duncan:
Cross-Modality Segmentation by Self-supervised Semantic Alignment in Disentangled Content Space. 52-61 - Haochuan Jiang, Agisilaos Chartsias, Xinheng Zhang, Giorgos Papanastasiou, Scott Semple, Mark R. Dweck, David Semple, Rohan Dharmakumar, Sotirios A. Tsaftaris:
Semi-supervised Pathology Segmentation with Disentangled Representations. 62-72 - Pulkit Khandelwal, Paul A. Yushkevich:
Domain Generalizer: A Few-Shot Meta Learning Framework for Domain Generalization in Medical Imaging. 73-84 - Ruibin Feng, Zongwei Zhou, Michael B. Gotway, Jianming Liang:
Parts2Whole: Self-supervised Contrastive Learning via Reconstruction. 85-95 - Tong Li, Kai Xuan, Zhong Xue, Lei Chen, Lichi Zhang, Dahong Qian:
Cross-View Label Transfer in Knee MR Segmentation Using Iterative Context Learning. 96-105 - Abdelrahman Elskhawy, Aneta Lisowska, Matthias Keicher, Joseph Henry, Paul Thomson, Nassir Navab:
Continual Class Incremental Learning for CT Thoracic Segmentation. 106-116 - Boris Shirokikh, Ivan Zakazov, Alexey Chernyavskiy, Irina Fedulova, Mikhail Belyaev:
First U-Net Layers Contain More Domain Specific Information Than the Last Ones. 117-126
DCL 2020
- Mathieu Andreux, Jean Ogier du Terrail, Constance Beguier, Eric W. Tramel:
Siloed Federated Learning for Multi-centric Histopathology Datasets. 129-139 - Mhd Hasan Sarhan, Nassir Navab, Abouzar Eslami, Shadi Albarqouni:
On the Fairness of Privacy-Preserving Representations in Medical Applications. 140-149 - Yousef Yeganeh, Azade Farshad, Nassir Navab, Shadi Albarqouni:
Inverse Distance Aggregation for Federated Learning with Non-IID Data. 150-159 - Felix Grimberg, Mary-Anne Hartley, Martin Jaggi, Sai Praneeth Karimireddy:
Weight Erosion: An Update Aggregation Scheme for Personalized Collaborative Machine Learning. 160-169 - Samuel W. Remedios, John A. Butman, Bennett A. Landman, Dzung L. Pham:
Federated Gradient Averaging for Multi-Site Training with Momentum-Based Optimizers. 170-180 - 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. 181-191 - Pochuan Wang, Chen Shen, Holger R. Roth, Dong Yang, Daguang Xu, Masahiro Oda, Kazunari Misawa, Po-Ting Chen, Kao-Lang Liu, Wei-Chih Liao, Weichung Wang, Kensaku Mori:
Automated Pancreas Segmentation Using Multi-institutional Collaborative Deep Learning. 192-200 - Santiago Silva, André Altmann, Boris Gutman, Marco Lorenzi:
Fed-BioMed: A General Open-Source Frontend Framework for Federated Learning in Healthcare. 201-210
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