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ORCID24th MICCAI 2021: Strasbourg, France - Part III
- Marleen de Bruijne
, Philippe C. Cattin, Stéphane Cotin, Nicolas Padoy, Stefanie Speidel, Yefeng Zheng, Caroline Essert:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27 - October 1, 2021, Proceedings, Part III. Lecture Notes in Computer Science 12903, Springer 2021, ISBN 978-3-030-87198-7
Machine Learning - Advances in Machine Learning Theory
- Laura Alexandra Daza, Juan C. Pérez, Pablo Arbeláez:
Towards Robust General Medical Image Segmentation. 3-13 - Shuo Wang, Chen Qin, Nicoló Savioli, Chen Chen, Declan P. O'Regan, Stuart A. Cook, Yike Guo, Daniel Rueckert, Wenjia Bai:
Joint Motion Correction and Super Resolution for Cardiac Segmentation via Latent Optimisation. 14-24 - Junyu Chen, Evren Asma, Chung Chan:
Targeted Gradient Descent: A Novel Method for Convolutional Neural Networks Fine-Tuning and Online-Learning. 25-35 - Qingsong Yao, Zecheng He, Yi Lin, Kai Ma, Yefeng Zheng, S. Kevin Zhou:
A Hierarchical Feature Constraint to Camouflage Medical Adversarial Attacks. 36-47 - Junjun He, Jin Ye, Cheng Li, Diping Song, Wanli Chen, Shanshan Wang, Lixu Gu, Yu Qiao:
Group Shift Pointwise Convolution for Volumetric Medical Image Segmentation. 48-58
Machine Learning - Attention Models
- Yunhe Gao, Mu Zhou, Dimitris N. Metaxas:
UTNet: A Hybrid Transformer Architecture for Medical Image Segmentation. 61-71 - Di You, Fenglin Liu, Shen Ge, Xiaoxia Xie, Jing Zhang, Xian Wu:
AlignTransformer: Hierarchical Alignment of Visual Regions and Disease Tags for Medical Report Generation. 72-82 - Jens Petersen, Fabian Isensee, Gregor Köhler, Paul F. Jäger, David Zimmerer, Ulf Neuberger, Wolfgang Wick, Jürgen Debus, Sabine Heiland, Martin Bendszus, Philipp Vollmuth, Klaus H. Maier-Hein:
Continuous-Time Deep Glioma Growth Models. 83-92 - Rong Tao, Guoyan Zheng:
Spine-Transformers: Vertebra Detection and Localization in Arbitrary Field-of-View Spine CT with Transformers. 93-103 - Gijs van Tulder, Yao Tong, Elena Marchiori:
Multi-view Analysis of Unregistered Medical Images Using Cross-View Transformers. 104-113
Machine Learning - Domain Adaptation
- Jia-Ren Chang, Min-Sheng Wu, Wei-Hsiang Yu, Chi-Chung Chen, Cheng-Kung Yang, Yen-Yu Lin, Chao-Yuan Yeh:
Stain Mix-Up: Unsupervised Domain Generalization for Histopathology Images. 117-126 - Heran Yang, Jian Sun, Liwei Yang, Zongben Xu:
A Unified Hyper-GAN Model for Unpaired Multi-contrast MR Image Translation. 127-137 - Xiaofeng Liu, Fangxu Xing, Maureen Stone, Jiachen Zhuo, Timothy G. Reese, Jerry L. Prince, Georges El Fakhri, Jonghye Woo:
Generative Self-training for Cross-Domain Unsupervised Tagged-to-Cine MRI Synthesis. 138-148 - Chen Chen, Kerstin Hammernik, Cheng Ouyang, Chen Qin, Wenjia Bai, Daniel Rueckert:
Cooperative Training and Latent Space Data Augmentation for Robust Medical Image Segmentation. 149-159 - Spyridon Thermos, Xiao Liu, Alison O'Neil, Sotirios A. Tsaftaris:
Controllable Cardiac Synthesis via Disentangled Anatomy Arithmetic. 160-170 - Yutong Xie, Jianpeng Zhang, Chunhua Shen, Yong Xia:
CoTr: Efficiently Bridging CNN and Transformer for 3D Medical Image Segmentation. 171-180 - Rongguang Wang, Pratik Chaudhari, Christos Davatzikos:
Harmonization with Flow-Based Causal Inference. 181-190 - Siqi Wu, Chang Chen, Zhiwei Xiong, Xuejin Chen, Xiaoyan Sun:
Uncertainty-Aware Label Rectification for Domain Adaptive Mitochondria Segmentation. 191-200 - Guodong Zeng, Till D. Lerch, Florian Schmaranzer, Guoyan Zheng, Jürgen Burger, Kate Gerber, Moritz Tannast, Klaus-Arno Siebenrock, Nicolas Gerber:
Semantic Consistent Unsupervised Domain Adaptation for Cross-Modality Medical Image Segmentation. 201-210 - Ivan Zakazov, Boris Shirokikh, Alexey Chernyavskiy, Mikhail Belyaev:
Anatomy of Domain Shift Impact on U-Net Layers in MRI Segmentation. 211-220 - Shawn Mathew, Saad Nadeem, Arie E. Kaufman:
FoldIt: Haustral Folds Detection and Segmentation in Colonoscopy Videos. 221-230 - Dan Hu, Weiyan Yin, Zhengwang Wu, Liangjun Chen, Li Wang, Weili Lin, Gang Li:
Reference-Relation Guided Autoencoder with Deep CCA Restriction for Awake-to-Sleep Brain Functional Connectome Prediction. 231-240 - Ran Gu, Jingyang Zhang, Rui Huang, Wenhui Lei, Guotai Wang, Shaoting Zhang:
Domain Composition and Attention for Unseen-Domain Generalizable Medical Image Segmentation. 241-250 - Minhao Hu, Tao Song, Yujun Gu, Xiangde Luo, Jieneng Chen, Yinan Chen, Ya Zhang, Shaoting Zhang:
Fully Test-Time Adaptation for Image Segmentation. 251-260 - Dawood Al Chanti, Diana Mateus:
OLVA: Optimal Latent Vector Alignment for Unsupervised Domain Adaptation in Medical Image Segmentation. 261-271 - Jie Liu, Xiaoqing Guo, Yixuan Yuan:
Prototypical Interaction Graph for Unsupervised Domain Adaptation in Surgical Instrument Segmentation. 272-281 - Seung Yeon Shin, Sungwon Lee, Ronald M. Summers:
Unsupervised Domain Adaptation for Small Bowel Segmentation Using Disentangled Representation. 282-292 - Javid Dadashkarimi, Amin Karbasi, Dustin Scheinost:
Data-Driven Mapping Between Functional Connectomes Using Optimal Transport. 293-302 - Numan Celik, Sharib Ali, Soumya Gupta, Barbara Braden, Jens Rittscher:
EndoUDA: A Modality Independent Segmentation Approach for Endoscopy Imaging. 303-312 - Mengting Liu, Piyush Maiti, Sophia I. Thomopoulos, Alyssa H. Zhu, Yaqiong Chai, Hosung Kim, Neda Jahanshad:
Style Transfer Using Generative Adversarial Networks for Multi-site MRI Harmonization. 313-322
Machine Learning - Federated Learning
- Quande Liu, Hongzheng Yang, Qi Dou, Pheng-Ann Heng:
Federated Semi-supervised Medical Image Classification via Inter-client Relation Matching. 325-335 - Tariq M. Bdair, Nassir Navab, Shadi Albarqouni:
FedPerl: Semi-supervised Peer Learning for Skin Lesion Classification. 336-346 - Zhen Chen, Meilu Zhu, Chen Yang, Yixuan Yuan:
Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning. 347-356 - Holger R. Roth, Dong Yang, Wenqi Li, Andriy Myronenko, Wentao Zhu, Ziyue Xu, Xiaosong Wang, Daguang Xu:
Federated Whole Prostate Segmentation in MRI with Personalized Neural Architectures. 357-366 - Yawen Wu, Dewen Zeng, Zhepeng Wang, Yiyu Shi, Jingtong Hu:
Federated Contrastive Learning for Volumetric Medical Image Segmentation. 367-377 - Nanqing Dong, Irina Voiculescu:
Federated Contrastive Learning for Decentralized Unlabeled Medical Images. 378-387
Machine Learning - Interpretability/Explainability
- Ashkan Khakzar, Yang Zhang, Wejdene Mansour, Yuezhi Cai, Yawei Li, Yucheng Zhang, Seong Tae Kim, Nassir Navab:
Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features. 391-401 - Chia-Hsiang Kao, Yong-Sheng Chen, Li-Fen Chen, Wei-Chen Chiu:
Demystifying T1-MRI to FDG18-PET Image Translation via Representational Similarity. 402-412 - Esther Puyol-Antón, Bram Ruijsink, Stefan K. Piechnik, Stefan Neubauer, Steffen E. Petersen, Reza Razavi, Andrew P. King:
Fairness in Cardiac MR Image Analysis: An Investigation of Bias Due to Data Imbalance in Deep Learning Based Segmentation. 413-423 - Anna Zapaishchykova, David Dreizin, Zhaoshuo Li, Jie Ying Wu, Shahrooz Faghihroohi, Mathias Unberath:
An Interpretable Approach to Automated Severity Scoring in Pelvic Trauma. 424-433 - Sebastian Pölsterl, Christina Aigner, Christian Wachinger:
Scalable, Axiomatic Explanations of Deep Alzheimer's Diagnosis from Heterogeneous Data. 434-444 - Amir Reza Sadri, Sepideh Azarianpour Esfahani, Prathyush Chirra, Jacob Antunes, Pavithran Pattiam Giriprakash, Patrick Leo, Anant Madabhushi, Satish E. Viswanath:
SPARTA: An Integrated Stability, Discriminability, and Sparsity Based Radiomic Feature Selection Approach. 445-455 - Vishwesh Nath, Dong Yang, Ali Hatamizadeh, Anas A. Abidin, Andriy Myronenko, Holger R. Roth, Daguang Xu:
The Power of Proxy Data and Proxy Networks for Hyper-parameter Optimization in Medical Image Segmentation. 456-465 - Yassine Marrakchi, Osama Makansi, Thomas Brox:
Fighting Class Imbalance with Contrastive Learning. 466-476 - Indu Ilanchezian, Dmitry Kobak, Hanna Faber, Focke Ziemssen, Philipp Berens, Murat Seçkin Ayhan:
Interpretable Gender Classification from Retinal Fundus Images Using BagNets. 477-487 - Michael Vasilakakis, Georgia Sovatzidi, Dimitris K. Iakovidis:
Explainable Classification of Weakly Annotated Wireless Capsule Endoscopy Images Based on a Fuzzy Bag-of-Colour Features Model and Brain Storm Optimization. 488-498 - Ashkan Khakzar, Sabrina Musatian, Jonas Buchberger, Icxel Valeriano Quiroz, Nikolaus Pinger, Soroosh Baselizadeh, Seong Tae Kim, Nassir Navab:
Towards Semantic Interpretation of Thoracic Disease and COVID-19 Diagnosis Models. 499-508 - Thomas Henn, Yasukazu Sakamoto, Clément Jacquet, Shunsuke Yoshizawa, Masamichi Andou, Stephen Tchen, Ryosuke Saga, Hiroyuki Ishihara, Katsuhiko Shimizu, Yingzhen Li, Ryutaro Tanno:
A Principled Approach to Failure Analysis and Model Repairment: Demonstration in Medical Imaging. 509-518 - Sumedha Singla, Stephen Wallace, Sofia Triantafillou, Kayhan Batmanghelich:
Using Causal Analysis for Conceptual Deep Learning Explanation. 519-528 - Sara Sedlar, Abib Alimi, Théodore Papadopoulo, Rachid Deriche, Samuel Deslauriers-Gauthier:
A Spherical Convolutional Neural Network for White Matter Structure Imaging via dMRI. 529-539 - Mara Graziani, Iam Palatnik de Sousa, Marley M. B. R. Vellasco, Eduardo Costa da Silva, Henning Müller, Vincent Andrearczyk:
Sharpening Local Interpretable Model-Agnostic Explanations for Histopathology: Improved Understandability and Reliability. 540-549 - Catarina Barata, Carlos Santiago:
Improving the Explainability of Skin Cancer Diagnosis Using CBIR. 550-559 - Anthony Sicilia, Xingchen Zhao, Anastasia Sosnovskikh, Seong Jae Hwang:
PAC Bayesian Performance Guarantees for Deep (Stochastic) Networks in Medical Imaging. 560-570
Machine Learning - Uncertainty
- Lin Wang, Lie Ju, Donghao Zhang, Xin Wang, Wanji He, Yelin Huang, Zhiwen Yang, Xuan Yao, Xin Zhao, Xiufen Ye, Zongyuan Ge:
Medical Matting: A New Perspective on Medical Segmentation with Uncertainty. 573-583 - Xukun Zhang, Zhiming Cui, Changan Chen, Jie Wei, Jingjiao Lou, Wenxin Hu, He Zhang, Tao Zhou, Feng Shi, Dinggang Shen:
Confidence-Aware Cascaded Network for Fetal Brain Segmentation on MR Images. 584-593 - Agostina J. Larrazabal, César Ernesto Martínez, Jose Dolz, Enzo Ferrante:
Orthogonal Ensemble Networks for Biomedical Image Segmentation. 594-603 - Shi Hu, Nicola Pezzotti, Max Welling:
Learning to Predict Error for MRI Reconstruction. 604-613 - Uddeshya Upadhyay, Yanbei Chen, Tobias Hepp, Sergios Gatidis, Zeynep Akata:
Uncertainty-Guided Progressive GANs for Medical Image Translation. 614-624 - Ivona Najdenkoska, Xiantong Zhen, Marcel Worring, Ling Shao:
Variational Topic Inference for Chest X-Ray Report Generation. 625-635 - James Browning, Micha Kornreich, Aubrey Chow, Jayashri Pawar, Li Zhang, Richard Herzog, Benjamin L. Odry:
Uncertainty Aware Deep Reinforcement Learning for Anatomical Landmark Detection in Medical Images. 636-644
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