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ORCID23rd MICCAI 2020: Lima, Peru - Part I
- Anne L. Martel
, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2020 - 23rd International Conference, Lima, Peru, October 4-8, 2020, Proceedings, Part I. Lecture Notes in Computer Science 12261, Springer 2020, ISBN 978-3-030-59709-2
Machine Learning Methodologies
- Haohan Li, Zhaozheng Yin:
Attention, Suggestion and Annotation: A Deep Active Learning Framework for Biomedical Image Segmentation. 3-13 - Hyeonsoo Lee, Won-Ki Jeong:
Scribble2Label: Scribble-Supervised Cell Segmentation via Self-generating Pseudo-Labels with Consistency. 14-23 - Christian Marzahl, Christof A. Bertram, Marc Aubreville, Anne Petrick, Kristina Weiler, Agnes C. Gläsel, Marco Fragoso, Sophie Merz, Florian Bartenschlager, Judith Hoppe, Alina Langenhagen, Anne-Katherine Jasensky, Jörn Voigt, Robert Klopfleisch, Andreas Maier:
Are Fast Labeling Methods Reliable? A Case Study of Computer-Aided Expert Annotations on Microscopy Slides. 24-32 - Jingwen Wang, Yuguang Yan, Yubing Zhang, Guiping Cao, Ming Yang, Michael K. Ng:
Deep Reinforcement Active Learning for Medical Image Classification. 33-42 - Quan Li, Yan Li, Xiaoyi Chen, Ni Zhang:
An Effective Data Refinement Approach for Upper Gastrointestinal Anatomy Recognition. 43-52 - Jiarong Ye, Yuan Xue, L. Rodney Long, Sameer K. Antani, Zhiyun Xue, Keith C. Cheng, Xiaolei Huang:
Synthetic Sample Selection via Reinforcement Learning. 53-63 - Wenzhe Wang, Qingyu Song, Jiarong Zhou, Ruiwei Feng, Tingting Chen, Wenhao Ge, Danny Z. Chen, S. Kevin Zhou, Weilin Wang, Jian Wu:
Dual-Level Selective Transfer Learning for Intrahepatic Cholangiocarcinoma Segmentation in Non-enhanced Abdominal CT. 64-73 - Tiange Xiang, Chaoyi Zhang, Dongnan Liu, Yang Song, Heng Huang, Weidong Cai:
BiO-Net: Learning Recurrent Bi-directional Connections for Encoder-Decoder Architecture. 74-84 - Weiyang Shi, Kaibin Xu, Ming Song, Lingzhong Fan, Tianzi Jiang:
Constrain Latent Space for Schizophrenia Classification via Dual Space Mapping Net. 85-94 - Xiao Liu, Sotirios A. Tsaftaris:
Have You Forgotten? A Method to Assess if Machine Learning Models Have Forgotten Data. 95-105 - Dong Wei, Shilei Cao, Kai Ma, Yefeng Zheng:
Learning and Exploiting Interclass Visual Correlations for Medical Image Classification. 106-115 - Rasha Sheikh, Thomas Schultz:
Feature Preserving Smoothing Provides Simple and Effective Data Augmentation for Medical Image Segmentation. 116-126 - Jiaxin Zhuang, Jiabin Cai, Ruixuan Wang, Jianguo Zhang, Wei-Shi Zheng:
Deep kNN for Medical Image Classification. 127-136 - Fatemeh Haghighi, Mohammad Reza Hosseinzadeh Taher, Zongwei Zhou, Michael B. Gotway, Jianming Liang:
Learning Semantics-Enriched Representation via Self-discovery, Self-classification, and Self-restoration. 137-147 - Aryan Mobiny, Pengyu Yuan, Pietro Antonio Cicalese, Hien Van Nguyen:
DECAPS: Detail-Oriented Capsule Networks. 148-158 - Daiqing Li, Amlan Kar, Nishant Ravikumar, Alejandro F. Frangi, Sanja Fidler:
Federated Simulation for Medical Imaging. 159-168 - Zhuoyun Li, Changhong Zhong, Ruixuan Wang, Wei-Shi Zheng:
Continual Learning of New Diseases with Dual Distillation and Ensemble Strategy. 169-178 - Le Zhang, Ryutaro Tanno, Kevin Bronik, Chen Jin, Parashkev Nachev, Frederik Barkhof, Olga Ciccarelli, Daniel C. Alexander:
Learning to Segment When Experts Disagree. 179-190 - Erkun Yang, Dongren Yao, Bing Cao, Hao Guan, Pew-Thian Yap, Dinggang Shen, Mingxia Liu:
Deep Disentangled Hashing with Momentum Triplets for Neuroimage Search. 191-201 - Alexandre Bône, Paul Vernhet, Olivier Colliot, Stanley Durrleman:
Learning Joint Shape and Appearance Representations with Metamorphic Auto-Encoders. 202-211 - Hui Cui, Yiyue Xu, Wanlong Li, Linlin Wang, Henry B. L. Duh:
Collaborative Learning of Cross-channel Clinical Attention for Radiotherapy-Related Esophageal Fistula Prediction from CT. 212-220 - Yulei Qin, Hao Zheng, Yun Gu, Xiaolin Huang, Jie Yang, Lihui Wang, Yue-Min Zhu:
Learning Bronchiole-Sensitive Airway Segmentation CNNs by Feature Recalibration and Attention Distillation. 221-231 - Chuanbin Liu, Hongtao Xie, Yunyan Yan, Zhendong Mao, Yongdong Zhang:
Learning Rich Attention for Pediatric Bone Age Assessment. 232-242 - Heng Guo, Minfeng Xu, Ying Chi, Lei Zhang, Xian-Sheng Hua:
Weakly Supervised Organ Localization with Attention Maps Regularized by Local Area Reconstruction. 243-252 - Fei Ding, Gang Yang, Jun Wu, Dayong Ding, Jie Xv, Gangwei Cheng, Xirong Li:
High-Order Attention Networks for Medical Image Segmentation. 253-262 - Zuhao Liu, Huan Wang, Shaoting Zhang, Guotai Wang, Jin Qi:
NAS-SCAM: Neural Architecture Search-Based Spatial and Channel Joint Attention Module for Nuclei Semantic Segmentation and Classification. 263-272 - Arunachalam Narayanaswamy, Subhashini Venugopalan, Dale R. Webster, Lily Peng, Gregory S. Corrado, Paisan Ruamviboonsuk, Pinal Bavishi, Michael P. Brenner, Philip C. Nelson, Avinash V. Varadarajan:
Scientific Discovery by Generating Counterfactuals Using Image Translation. 273-283 - Esther Puyol-Antón, Chen Chen, James R. Clough, Bram Ruijsink, Baldeep S. Sidhu, Justin Gould, Bradley Porter, Mark K. Elliott, Vishal Mehta, Daniel Rueckert, Christopher A. Rinaldi, Andrew P. King:
Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction. 284-293 - Rodney LaLonde, Drew A. Torigian, Ulas Bagci:
Encoding Visual Attributes in Capsules for Explainable Medical Diagnoses. 294-304 - Wilson Silva, Alexander Pollinger, Jaime S. Cardoso, Mauricio Reyes:
Interpretability-Guided Content-Based Medical Image Retrieval. 305-314 - Dimitrios Lenis, David Major, Maria Wimmer, Astrid Berg, Gert Sluiter, Katja Bühler:
Domain Aware Medical Image Classifier Interpretation by Counterfactual Impact Analysis. 315-325 - Alberto Santamaría-Pang, James Kubricht, Aritra Chowdhury, Chitresh Bhushan, Peter H. Tu:
Towards Emergent Language Symbolic Semantic Segmentation and Model Interpretability. 326-334 - Jixin Wang, Sanping Zhou, Chaowei Fang, Le Wang, Jinjun Wang:
Meta Corrupted Pixels Mining for Medical Image Segmentation. 335-345 - Yuanfeng Ji, Ruimao Zhang, Zhen Li, Jiamin Ren, Shaoting Zhang, Ping Luo:
UXNet: Searching Multi-level Feature Aggregation for 3D Medical Image Segmentation. 346-356 - Xiaomeng Li, Lequan Yu, Yueming Jin, Chi-Wing Fu, Lei Xing, Pheng-Ann Heng:
Difficulty-Aware Meta-learning for Rare Disease Diagnosis. 357-366 - Pengyu Yuan, Aryan Mobiny, Jahandar Jahanipour, Xiaoyang Li, Pietro Antonio Cicalese, Badrinath Roysam, Vishal M. Patel, Maric Dragan, Hien Van Nguyen:
Few Is Enough: Task-Augmented Active Meta-learning for Brain Cell Classification. 367-377 - Ju Xu, Mengzhang Li, Zhanxing Zhu:
Automatic Data Augmentation for 3D Medical Image Segmentation. 378-387 - Xingang Yan, Weiwen Jiang, Yiyu Shi, Cheng Zhuo:
MS-NAS: Multi-scale Neural Architecture Search for Medical Image Segmentation. 388-397 - Hong-Yu Zhou, Shuang Yu, Cheng Bian, Yifan Hu, Kai Ma, Yefeng Zheng:
Comparing to Learn: Surpassing ImageNet Pretraining on Radiographs by Comparing Image Representations. 398-407 - Yingying Xue, Shixiang Feng, Ya Zhang, Xiaoyun Zhang, Yanfeng Wang:
Dual-Task Self-supervision for Cross-modality Domain Adaptation. 408-417 - Kang Li, Shujun Wang, Lequan Yu, Pheng-Ann Heng:
Dual-Teacher: Integrating Intra-domain and Inter-domain Teachers for Annotation-Efficient Cardiac Segmentation. 418-427 - Thomas Varsavsky, Mauricio Orbes-Arteaga, Carole H. Sudre, Mark S. Graham, Parashkev Nachev, M. Jorge Cardoso:
Test-Time Unsupervised Domain Adaptation. 428-436 - Yufan He, Aaron Carass, Lianrui Zuo, Blake E. Dewey, Jerry L. Prince:
Self Domain Adapted Network. 437-446 - Guodong Zeng, Florian Schmaranzer, Till D. Lerch, Adam Boschung, Guoyan Zheng, Jürgen Burger, Kate Gerber, Moritz Tannast, Klaus-Arno Siebenrock, Young-Jo Kim, Eduardo N. Novais, Nicolas Gerber:
Entropy Guided Unsupervised Domain Adaptation for Cross-Center Hip Cartilage Segmentation from MRI. 447-456 - Ashwin Raju, Zhanghexuan Ji, Chi-Tung Cheng, Jinzheng Cai, Junzhou Huang, Jing Xiao, Le Lu, Chien-Hung Liao, Adam P. Harrison:
User-Guided Domain Adaptation for Rapid Annotation from User Interactions: A Study on Pathological Liver Segmentation. 457-467 - Behzad Bozorgtabar, Dwarikanath Mahapatra, Guillaume Vray, Jean-Philippe Thiran:
SALAD: Self-supervised Aggregation Learning for Anomaly Detection on X-Rays. 468-478 - Reuben Dorent, Samuel Joutard, Jonathan Shapey, Sotirios Bisdas, Neil Kitchen, Robert Bradford, Shakeel R. Saeed, Marc Modat, Sébastien Ourselin, Tom Vercauteren:
Scribble-Based Domain Adaptation via Co-segmentation. 479-489 - Mathilde Bateson, Hoel Kervadec, Jose Dolz, Hervé Lombaert, Ismail Ben Ayed:
Source-Relaxed Domain Adaptation for Image Segmentation. 490-499 - Subhradeep Kayal, Shuai Chen, Marleen de Bruijne:
Region-of-Interest Guided Supervoxel Inpainting for Self-supervision. 500-509 - Eleni Chiou, Francesco Giganti, Shonit Punwani, Iasonas Kokkinos, Eleftheria Panagiotaki:
Harnessing Uncertainty in Domain Adaptation for MRI Prostate Lesion Segmentation. 510-520 - Yanning Zhou, Hao Chen, Huangjing Lin, Pheng-Ann Heng:
Deep Semi-supervised Knowledge Distillation for Overlapping Cervical Cell Instance Segmentation. 521-531 - Kang Fang, Wu-Jun Li:
DMNet: Difference Minimization Network for Semi-supervised Segmentation in Medical Images. 532-541 - Yixin Wang, Yao Zhang, Jiang Tian, Cheng Zhong, Zhongchao Shi, Yang Zhang, Zhiqiang He:
Double-Uncertainty Weighted Method for Semi-supervised Learning. 542-551 - Shuailin Li, Chuyu Zhang, Xuming He:
Shape-Aware Semi-supervised 3D Semantic Segmentation for Medical Images. 552-561 - Wenlong Hang, Wei Feng, Shuang Liang, Lequan Yu, Qiong Wang, Kup-Sze Choi, Jing Qin:
Local and Global Structure-Aware Entropy Regularized Mean Teacher Model for 3D Left Atrium Segmentation. 562-571 - Minh Nguyen Nhat To, Sandeep Sankineni, Sheng Xu, Baris Turkbey, Peter A. Pinto, Vanessa Moreno, María Merino, Bradford J. Wood, Jin Tae Kwak:
Improving Dense Pixelwise Prediction of Epithelial Density Using Unsupervised Data Augmentation for Consistency Regularization. 572-581 - Huan Qi, Sally L. Collins, J. Alison Noble:
Knowledge-Guided Pretext Learning for Utero-Placental Interface Detection. 582-593 - Fengbei Liu, Yaqub Jonmohamadi, Gabriel Maicas, Ajay K. Pandey, Gustavo Carneiro:
Self-supervised Depth Estimation to Regularise Semantic Segmentation in Knee Arthroscopy. 594-603 - Prashnna Kumar Gyawali, Sandesh Ghimire, Pradeep Bajracharya, Zhiyuan Li, Linwei Wang:
Semi-supervised Medical Image Classification with Global Latent Mixing. 604-613 - Yuexiang Li, Jiawei Chen, Xinpeng Xie, Kai Ma, Yefeng Zheng:
Self-Loop Uncertainty: A Novel Pseudo-Label for Semi-supervised Medical Image Segmentation. 614-623 - Balagopal Unnikrishnan, Cuong Manh Nguyen, Shafa Balaram, Chuan Sheng Foo, Pavitra Krishnaswamy:
Semi-supervised Classification of Diagnostic Radiographs with NoTeacher: A Teacher that is Not Mean. 624-634 - Alireza Ganjdanesh, Kamran Ghasedi, Liang Zhan, Weidong Cai, Heng Huang:
Predicting Potential Propensity of Adolescents to Drugs via New Semi-supervised Deep Ordinal Regression Model. 635-645 - Hongxu Yang, Caifeng Shan, Alexander F. Kolen, Peter H. N. de With:
Deep Q-Network-Driven Catheter Segmentation in 3D US by Hybrid Constrained Semi-supervised Learning and Dual-UNet. 646-655 - Shuhao Fu, Yongyi Lu, Yan Wang, Yuyin Zhou, Wei Shen, Elliot K. Fishman, Alan L. Yuille:
Domain Adaptive Relational Reasoning for 3D Multi-organ Segmentation. 656-666 - Chen Chen, Chen Qin, Huaqi Qiu, Cheng Ouyang, Shuo Wang, Liang Chen, Giacomo Tarroni, Wenjia Bai, Daniel Rueckert:
Realistic Adversarial Data Augmentation for MR Image Segmentation. 667-677 - Yuhang Lu, Weijian Li, Kang Zheng, Yirui Wang, Adam P. Harrison, Chihung Lin, Song Wang, Jing Xiao, Le Lu, Chang-Fu Kuo, Shun Miao:
Learning to Segment Anatomical Structures Accurately from One Exemplar. 678-688 - Lorenzo Venturini, Aris T. Papageorghiou, J. Alison Noble, Ana I. L. Namburete:
Uncertainty Estimates as Data Selection Criteria to Boost Omni-Supervised Learning. 689-698 - Gaurav Fotedar, Nima Tajbakhsh, Shilpa P. Ananth, Xiaowei Ding:
Extreme Consistency: Overcoming Annotation Scarcity and Domain Shifts. 699-709 - Vanessa Gonzalez Duque, Dawood Al Chanti, Marion Crouzier, Antoine Nordez, Lilian Lacourpaille, Diana Mateus:
Spatio-Temporal Consistency and Negative Label Transfer for 3D Freehand US Segmentation. 710-720 - Minqing Zhang, Jiantao Gao, Zhen Lyu, Weibing Zhao, Qin Wang, Weizhen Ding, Sheng Wang, Zhen Li, Shuguang Cui:
Characterizing Label Errors: Confident Learning for Noisy-Labeled Image Segmentation. 721-730 - Junde Wu, Shuang Yu, Wenting Chen, Kai Ma, Rao Fu, Hanruo Liu, Xiaoguang Di, Yefeng Zheng:
Leveraging Undiagnosed Data for Glaucoma Classification with Teacher-Student Learning. 731-740 - Shuang Yu, Hong-Yu Zhou, Kai Ma, Cheng Bian, Chunyan Chu, Hanruo Liu, Yefeng Zheng:
Difficulty-Aware Glaucoma Classification with Multi-rater Consensus Modeling. 741-750 - William Mandel, Stefan Parent, Samuel Kadoury:
Intra-operative Forecasting of Growth Modulation Spine Surgery Outcomes with Spatio-Temporal Dynamic Networks. 751-760 - Vinkle Srivastav, Afshin Gangi, Nicolas Padoy:
Self-supervision on Unlabelled or Data for Multi-person 2D/3D Human Pose Estimation. 761-771 - Minhao Hu, Matthis Maillard, Ya Zhang, Tommaso Ciceri, Giammarco La Barbera, Isabelle Bloch, Pietro Gori:
Knowledge Distillation from Multi-modal to Mono-modal Segmentation Networks. 772-781 - Ziyi Huang, Yu Gan, Theresa Lye, Haofeng Zhang, Andrew Laine, Elsa D. Angelini, Christine P. Hendon:
Heterogeneity Measurement of Cardiac Tissues Leveraging Uncertainty Information from Image Segmentation. 782-791 - Xiaoxiao Li, Yuan Zhou, Nicha C. Dvornek, Yufeng Gu, Pamela Ventola, James S. Duncan:
Efficient Shapley Explanation for Features Importance Estimation Under Uncertainty. 792-801 - Hao Zheng, Susan M. Motch Perrine, M. Kathleen Pitirri, Kazuhiko Kawasaki, Chaoli Wang, Joan T. Richtsmeier, Danny Z. Chen:
Cartilage Segmentation in High-Resolution 3D Micro-CT Images via Uncertainty-Guided Self-training with Very Sparse Annotation. 802-812 - Katarína Tóthová, Sarah Parisot, Matthew C. H. Lee, Esther Puyol-Antón, Andrew P. King, Marc Pollefeys, Ender Konukoglu:
Probabilistic 3D Surface Reconstruction from Sparse MRI Information. 813-823 - Jeppe Thagaard, Søren Hauberg, Bert van der Vegt, Thomas Ebstrup, Johan D. Hansen, Anders B. Dahl:
Can You Trust Predictive Uncertainty Under Real Dataset Shifts in Digital Pathology? 824-833 - Matt Hemsley, Brige Chugh, Mark Ruschin, Young Lee, Chia-Lin Tseng, Greg J. Stanisz, Angus Lau:
Deep Generative Model for Synthetic-CT Generation with Uncertainty Predictions. 834-844
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