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ORCID3rd DART / 1st FAIR @ MICCAI 2021: Strasbourg, France
- Shadi Albarqouni
, Manuel Jorge Cardoso, Qi Dou, Konstantinos Kamnitsas, Bishesh Khanal, Islem Rekik, Nicola Rieke, Debdoot Sheet, Sotirios A. Tsaftaris, Daguang Xu, Ziyue Xu:
Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health - Third MICCAI Workshop, DART 2021, and First MICCAI Workshop, FAIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings. Lecture Notes in Computer Science 12968, Springer 2021, ISBN 978-3-030-87721-7
Domain Adaptation and Representation Transfer
- Mohammad Reza Hosseinzadeh Taher, Fatemeh Haghighi, Ruibin Feng, Michael B. Gotway, Jianming Liang:
A Systematic Benchmarking Analysis of Transfer Learning for Medical Image Analysis. 3-13 - Gabriele Valvano, Andrea Leo, Sotirios A. Tsaftaris:
Self-supervised Multi-scale Consistency for Weakly Supervised Segmentation Learning. 14-24 - Minghui Zhang, Xin Yu, Hanxiao Zhang, Hao Zheng, Weihao Yu, Hong Pan, Xiangran Cai, Yun Gu:
FDA: Feature Decomposition and Aggregation for Robust Airway Segmentation. 25-34 - Marius Memmel, Camila González, Anirban Mukhopadhyay:
Adversarial Continual Learning for Multi-domain Hippocampal Segmentation. 35-45 - Dwarikanath Mahapatra, Behzad Bozorgtabar, Shiba Kuanar, Zongyuan Ge:
Self-supervised Multimodal Generalized Zero Shot Learning for Gleason Grading. 46-56 - Dwarikanath Mahapatra, Shiba Kuanar, Behzad Bozorgtabar, Zongyuan Ge:
Self-supervised Learning of Inter-label Geometric Relationships for Gleason Grade Segmentation. 57-67 - Gabriele Valvano, Andrea Leo, Sotirios A. Tsaftaris:
Stop Throwing Away Discriminators! Re-using Adversaries for Test-Time Training. 68-78 - Konstantinos Kamnitsas, Stefan Winzeck, Evgenios N. Kornaropoulos, Daniel Whitehouse, Cameron Englman, Poe Phyu, Norman Pao, David K. Menon, Daniel Rueckert, Tilak Das, Virginia F. J. Newcombe, Ben Glocker:
Transductive Image Segmentation: Self-training and Effect of Uncertainty Estimation. 79-89 - Eleni Chiou, Francesco Giganti, Shonit Punwani, Iasonas Kokkinos, Eleftheria Panagiotaki:
Unsupervised Domain Adaptation with Semantic Consistency Across Heterogeneous Modalities for MRI Prostate Lesion Segmentation. 90-100 - Brennan Nichyporuk, Jillian Cardinell, Justin Szeto, Raghav Mehta, Sotirios A. Tsaftaris, Douglas L. Arnold, Tal Arbel:
Cohort Bias Adaptation in Aggregated Datasets for Lesion Segmentation. 101-111 - Théo Estienne, Maria Vakalopoulou, Stergios Christodoulidis, Enzo Battistella, Théophraste Henry, Marvin Lerousseau, Amaury Leroy, Guillaume Chassagnon, Marie-Pierre Revel, Nikos Paragios, Eric Deutsch:
Exploring Deep Registration Latent Spaces. 112-122 - Gregory Filbrandt, Konstantinos Kamnitsas, David Bernstein, Alexandra Taylor, Ben Glocker:
Learning from Partially Overlapping Labels: Image Segmentation Under Annotation Shift. 123-132 - Ziyu Ye, Chen Ju, Chaofan Ma, Xiaoyun Zhang:
Unsupervised Domain Adaption via Similarity-Based Prototypes for Cross-Modality Segmentation. 133-143
Affordable AI and Healthcare
- Rija Tonny Christian Ramarolahy, Esther Opoku Gyasi, Alessandro Crimi:
Classification and Generation of Microscopy Images with Plasmodium Falciparum via Artificial Neural Networks Using Low Cost Settings. 147-157 - Shujaat Khan, Jaeyoung Huh, Jong Chul Ye:
Contrast and Resolution Improvement of POCUS Using Self-consistent CycleGAN. 158-167 - Viswanath P. Sudarshan, Athulkumar R, K. Pavan Kumar Reddy, Jayavardhana Gubbi, Balamuralidhar Purushothaman:
Low-Dose Dynamic CT Perfusion Denoising Without Training Data. 168-179 - Alpay Tekin, Ahmed Nebli, Islem Rekik:
Recurrent Brain Graph Mapper for Predicting Time-Dependent Brain Graph Evaluation Trajectory. 180-190 - Alexander MacLean, Saad Abbasi, Ashkan Ebadi, Andy Zhao, Maya Pavlova, Hayden Gunraj, Pengcheng Xi, Sonny Kohli, Alexander Wong:
COVID-Net US: A Tailored, Highly Efficient, Self-attention Deep Convolutional Neural Network Design for Detection of COVID-19 Patient Cases from Point-of-Care Ultrasound Imaging. 191-202 - Basar Demir, Alaa Bessadok, Islem Rekik:
Inter-domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student Learning. 203-215 - Ario Sadafi, Asya Makhro, Leonid Livshits, Nassir Navab, Anna Bogdanova, Shadi Albarqouni, Carsten Marr:
Sickle Cell Disease Severity Prediction from Percoll Gradient Images Using Graph Convolutional Networks. 216-225 - Shikhar Srivastava, Mohammad Yaqub, Karthik Nandakumar, Zongyuan Ge, Dwarikanath Mahapatra:
Continual Domain Incremental Learning for Chest X-Ray Classification in Low-Resource Clinical Settings. 226-238 - Vikash Gupta, Clayton Taylor, Sarah Bonnet, Luciano M. Prevedello, Jeffrey Hawley, Richard D. White, Mona G. Flores, Barbaros Selnur Erdal:
Deep Learning Based Automatic Detection of Adequately Positioned Mammograms. 239-250 - Samuel Budd, Thomas G. Day, John M. Simpson, Karen Lloyd, Jacqueline Matthew, Emily Skelton, Reza Razavi, Bernhard Kainz:
Can Non-specialists Provide High Quality Gold Standard Labels in Challenging Modalities? 251-262
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