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ORCID24th MICCAI 2021: Strasbourg, France - Part I
- 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 I. Lecture Notes in Computer Science 12901, Springer 2021, ISBN 978-3-030-87192-5
Image Segmentation
- Zhe Xu, Donghuan Lu, Yixin Wang, Jie Luo, Jagadeesan Jayender, Kai Ma, Yefeng Zheng, Xiu Li:
Noisy Labels are Treasure: Mean-Teacher-Assisted Confident Learning for Hepatic Vessel Segmentation. 3-13 - Yundong Zhang, Huiye Liu, Qiang Hu:
TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation. 14-24 - Yucheng Tang, Riqiang Gao, Ho Hin Lee, Qi Yang, Xin Yu, Yuyin Zhou, Shunxing Bao, Yuankai Huo, Jeffrey M. Spraggins, Jack Virostko, Zhoubing Xu, Bennett A. Landman:
Pancreas CT Segmentation by Predictive Phenotyping. 25-35 - Jeya Maria Jose Valanarasu, Poojan Oza, Ilker Hacihaliloglu, Vishal M. Patel:
Medical Transformer: Gated Axial-Attention for Medical Image Segmentation. 36-46 - Bo Zhou, Chi Liu, James S. Duncan:
Anatomy-Constrained Contrastive Learning for Synthetic Segmentation Without Ground-Truth. 47-56 - Yuqian Zhou, Hanchao Yu, Humphrey Shi:
Study Group Learning: Improving Retinal Vessel Segmentation Trained with Noisy Labels. 57-67 - Yue Zhang, Chengtao Peng, Liying Peng, Huimin Huang, Ruofeng Tong, Lanfen Lin, Jingsong Li, Yen-Wei Chen, Qingqing Chen, Hongjie Hu, Zhiyi Peng:
Multi-phase Liver Tumor Segmentation with Spatial Aggregation and Uncertain Region Inpainting. 68-77 - Davood Karimi, Serge Vasylechko, Ali Gholipour:
Convolution-Free Medical Image Segmentation Using Transformers. 78-88 - Jie Wei, Feng Shi, Zhiming Cui, Yongsheng Pan, Yong Xia, Dinggang Shen:
Consistent Segmentation of Longitudinal Brain MR Images with Spatio-Temporal Constrained Networks. 89-98 - Yinglin Zhang, Risa Higashita, Huazhu Fu, Yanwu Xu, Yang Zhang, Haofeng Liu, Jian Zhang, Jiang Liu:
A Multi-branch Hybrid Transformer Network for Corneal Endothelial Cell Segmentation. 99-108 - Wenxuan Wang, Chen Chen, Meng Ding, Hong Yu, Sen Zha, Jiangyun Li:
TransBTS: Multimodal Brain Tumor Segmentation Using Transformer. 109-119 - Xiaoqi Zhao, Lihe Zhang, Huchuan Lu:
Automatic Polyp Segmentation via Multi-scale Subtraction Network. 120-130 - Hongyi Wang, Lanfen Lin, Hongjie Hu, Qingqing Chen, Yinhao Li, Yutaro Iwamoto, Xian-Hua Han, Yen-Wei Chen, Ruofeng Tong:
Patch-Free 3D Medical Image Segmentation Driven by Super-Resolution Technique and Self-Supervised Guidance. 131-141 - Ge-Peng Ji, Yu-Cheng Chou, Deng-Ping Fan, Geng Chen, Huazhu Fu, Debesh Jha, Ling Shao:
Progressively Normalized Self-Attention Network for Video Polyp Segmentation. 142-152 - Zimeng Tan, Jianjiang Feng, Jie Zhou:
SGNet: Structure-Aware Graph-Based Network for Airway Semantic Segmentation. 153-163 - Zudi Lin, Donglai Wei, Mariela D. Petkova, Yuelong Wu, Zergham Ahmed, Krishna Swaroop K, Silin Zou, Nils Wendt, Jonathan Boulanger-Weill, Xueying Wang, Nagaraju Dhanyasi, Ignacio Arganda-Carreras, Florian Engert, Jeff Lichtman, Hanspeter Pfister:
NucMM Dataset: 3D Neuronal Nuclei Instance Segmentation at Sub-Cubic Millimeter Scale. 164-174 - Donglai Wei, Kisuk Lee, Hanyu Li, Ran Lu, J. Alexander Bae, Zequan Liu, Lifu Zhang, Márcia dos Santos, Zudi Lin, Thomas D. Uram, Xueying Wang, Ignacio Arganda-Carreras, Brian Matejek, Narayanan Kasthuri, Jeff Lichtman, Hanspeter Pfister:
AxonEM Dataset: 3D Axon Instance Segmentation of Brain Cortical Regions. 175-185 - Chenghao Liu, Xiangzhu Zeng, Kongming Liang, Yizhou Yu, Chuyang Ye:
Improved Brain Lesion Segmentation with Anatomical Priors from Healthy Subjects. 186-195 - Xinru Zhang, Chenghao Liu, Ni Ou, Xiangzhu Zeng, Xiaoliang Xiong, Yizhou Yu, Zhiwen Liu, Chuyang Ye:
CarveMix: A Simple Data Augmentation Method for Brain Lesion Segmentation. 196-205 - Jiacheng Wang, Lan Wei, Liansheng Wang, Qichao Zhou, Lei Zhu, Jing Qin:
Boundary-Aware Transformers for Skin Lesion Segmentation. 206-216 - Jiaqi Yang, Xiaoling Hu, Chao Chen, Chialing Tsai:
A Topological-Attention ConvLSTM Network and Its Application to EM Images. 217-228 - Xinyi Wang, Tiange Xiang, Chaoyi Zhang, Yang Song, Dongnan Liu, Heng Huang, Weidong Cai:
BiX-NAS: Searching Efficient Bi-directional Architecture for Medical Image Segmentation. 229-238 - Arnaud Boutillon, Pierre-Henri Conze, Christelle Pons, Valérie Burdin, Bhushan Borotikar:
Multi-task, Multi-domain Deep Segmentation with Shared Representations and Contrastive Regularization for Sparse Pediatric Datasets. 239-249 - Madeleine K. Wyburd, Nicola K. Dinsdale, Ana I. L. Namburete, Mark Jenkinson:
TEDS-Net: Enforcing Diffeomorphisms in Spatial Transformers to Guarantee Topology Preservation in Segmentations. 250-260 - Lei Li, Sheng Lian, Zhiming Luo, Shaozi Li, Beizhan Wang, Shuo Li:
Learning Consistency- and Discrepancy-Context for 2D Organ Segmentation. 261-270 - Yanyu Xu, Xinxing Xu, Lei Jin, Shenghua Gao, Rick Siow Mong Goh, Daniel Shu Wei Ting, Yong Liu:
Partially-Supervised Learning for Vessel Segmentation in Ocular Images. 271-281 - Liang Han, Zhaozheng Yin:
Unsupervised Network Learning for Cell Segmentation. 282-292 - Ziyuan Zhao, Kaixin Xu, Shumeng Li, Zeng Zeng, Cuntai Guan:
MT-UDA: Towards Unsupervised Cross-modality Medical Image Segmentation with Limited Source Labels. 293-303 - Ping Wang, Jizong Peng, Marco Pedersoli, Yuanfeng Zhou, Caiming Zhang, Christian Desrosiers:
Context-Aware Virtual Adversarial Training for Anatomically-Plausible Segmentation. 304-314 - Helena Williams, João Pedrosa, Laura Cattani, Susanne Housmans, Tom Vercauteren, Jan Deprest, Jan D'hooge:
Interactive Segmentation via Deep Learning and B-Spline Explicit Active Surfaces. 315-325 - Yuanfeng Ji, Ruimao Zhang, Huijie Wang, Zhen Li, Lingyun Wu, Shaoting Zhang, Ping Luo:
Multi-compound Transformer for Accurate Biomedical Image Segmentation. 326-336 - Pengfei Gu, Hao Zheng, Yizhe Zhang, Chaoli Wang, Danny Z. Chen:
kCBAC-Net: Deeply Supervised Complete Bipartite Networks with Asymmetric Convolutions for Medical Image Segmentation. 337-347 - Shawn S. Ahn, Kevinminh Ta, Stephanie Thorn, Jonathan Langdon, Albert J. Sinusas, James S. Duncan:
Multi-frame Attention Network for Left Ventricle Segmentation in 3D Echocardiography. 348-357 - Qiankun Ma, Chen Zu, Xi Wu, Jiliu Zhou, Yan Wang:
Coarse-To-Fine Segmentation of Organs at Risk in Nasopharyngeal Carcinoma Radiotherapy. 358-368 - Hongwei Zhang, Dong Zhang, Zhifan Gao, Heye Zhang:
Joint Segmentation and Quantification of Main Coronary Vessels Using Dual-Branch Multi-scale Attention Network. 369-378 - Euijoon Ahn, Dagan Feng, Jinman Kim:
A Spatial Guided Self-supervised Clustering Network for Medical Image Segmentation. 379-388 - Jingyang Zhang, Ran Gu, Guotai Wang, Lixu Gu:
Comprehensive Importance-Based Selective Regularization for Continual Segmentation Across Multiple Sites. 389-399 - Miika Toikkanen, Doyoung Kwon, Minho Lee:
ReSGAN: Intracranial Hemorrhage Segmentation with Residuals of Synthetic Brain CT Scans. 400-409 - Hao Zheng, Yulei Qin, Yun Gu, Fangfang Xie, Jiayuan Sun, Jie Yang, Guang-Zhong Yang:
Refined Local-imbalance-based Weight for Airway Segmentation in CT. 410-419 - Youyi Song, Lequan Yu, Baiying Lei, Kup-Sze Choi, Jing Qin:
Selective Learning from External Data for CT Image Segmentation. 420-430 - Dmitrii A. Lachinov, Philipp Seeböck, Julia Mai, Felix Goldbach, Ursula Schmidt-Erfurth, Hrvoje Bogunovic:
Projective Skip-Connections for Segmentation Along a Subset of Dimensions in Retinal OCT. 431-441 - Ziqi Yu, Yuting Zhai, Xiaoyang Han, Tingying Peng, Xiao-Yong Zhang:
MouseGAN: GAN-Based Multiple MRI Modalities Synthesis and Segmentation for Mouse Brain Structures. 442-450 - Zhendong Liu, Manh The Van, Xin Yang, Xiaoqiong Huang, Karim Lekadir, Víctor M. Campello, Nishant Ravikumar, Alejandro F. Frangi, Dong Ni:
Style Curriculum Learning for Robust Medical Image Segmentation. 451-460 - Yukun Ding, Dewen Zeng, Mingqi Li, Hongwen Fei, Haiyun Yuan, Meiping Huang, Jian Zhuang, Yiyu Shi:
Towards Efficient Human-Machine Collaboration: Real-Time Correction Effort Prediction for Ultrasound Data Acquisition. 461-470 - Ke Wang, Shujun Liang, Yu Zhang:
Residual Feedback Network for Breast Lesion Segmentation in Ultrasound Image. 471-481 - Yukun Zhou, Moucheng Xu, Yipeng Hu, Hongxiang Lin, Joseph Jacob, Pearse A. Keane, Daniel C. Alexander:
Learning to Address Intra-segment Misclassification in Retinal Imaging. 482-492 - Yuhao Huang, Xin Yang, Yuxin Zou, Chaoyu Chen, Jian Wang, Haoran Dou, Nishant Ravikumar, Alejandro F. Frangi, Jianqiao Zhou, Dong Ni:
Flip Learning: Erase to Segment. 493-502 - Rongtao Xu, Changwei Wang, Shibiao Xu, Weiliang Meng, Xiaopeng Zhang:
DC-Net: Dual Context Network for 2D Medical Image Segmentation. 503-513 - Dewei Hu, Can Cui, Hao Li, Kathleen E. Larson, Yuankai K. Tao, Ipek Oguz:
LIFE: A Generalizable Autodidactic Pipeline for 3D OCT-A Vessel Segmentation. 514-524 - Shuailin Li, Zhitong Gao, Xuming He:
Superpixel-Guided Iterative Learning from Noisy Labels for Medical Image Segmentation. 525-535 - Mingyan Qiu, Chenxi Zhang, Zhijian Song:
A Hybrid Attention Ensemble Framework for Zonal Prostate Segmentation. 536-547 - Tan Nguyen, Binh-Son Hua, Ngan Le:
3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation. 548-558 - Yantao Shen, Xiao Jia, Max Q.-H. Meng:
HRENet: A Hard Region Enhancement Network for Polyp Segmentation. 559-568 - Zijie Chen, Cheng Li, Junjun He, Jin Ye, Diping Song, Shanshan Wang, Lixu Gu, Yu Qiao:
A Novel Hybrid Convolutional Neural Network for Accurate Organ Segmentation in 3D Head and Neck CT Images. 569-578 - Jiawei Yang, Yao Zhang, Yuan Liang, Yang Zhang, Lei He, Zhiqiang He:
TumorCP: A Simple but Effective Object-Level Data Augmentation for Tumor Segmentation. 579-588 - Yao Zhang, Jiawei Yang, Jiang Tian, Zhongchao Shi, Cheng Zhong, Yang Zhang, Zhiqiang He:
Modality-Aware Mutual Learning for Multi-modal Medical Image Segmentation. 589-599 - Nicolás Gaggion, Lucas Mansilla, Diego H. Milone, Enzo Ferrante:
Hybrid Graph Convolutional Neural Networks for Landmark-Based Anatomical Segmentation. 600-610 - Jiancheng Yang, Shixuan Gu, Donglai Wei, Hanspeter Pfister, Bingbing Ni:
RibSeg Dataset and Strong Point Cloud Baselines for Rib Segmentation from CT Scans. 611-621 - Hao Zheng, Jun Han, Hongxiao Wang, Lin Yang, Zhuo Zhao, Chaoli Wang, Danny Z. Chen:
Hierarchical Self-supervised Learning for Medical Image Segmentation Based on Multi-domain Data Aggregation. 622-632 - Tan-Cong Nguyen, Tien-Phat Nguyen, Gia-Han Diep, Anh-Huy Tran-Dinh, Tam V. Nguyen, Minh-Triet Tran:
CCBANet: Cascading Context and Balancing Attention for Polyp Segmentation. 633-643 - Ngoc-Vuong Ho, Tan Nguyen, Gia-Han Diep, Ngan Le, Binh-Son Hua:
Point-Unet: A Context-Aware Point-Based Neural Network for Volumetric Segmentation. 644-655 - Atefeh Shahroudnejad, Xuebin Qin, Sharanya Balachandran, Masood Dehghan, Dornoosh Zonoobi, Jacob L. Jaremko, Jeevesh Kapur, Martin Jägersand, Michelle Noga, Kumaradevan Punithakumar:
TUN-Det: A Novel Network for Thyroid Ultrasound Nodule Detection. 656-667 - Jialin Shi, Ji Wu:
Distilling Effective Supervision for Robust Medical Image Segmentation with Noisy Labels. 668-677 - Teodora Popordanoska, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Matthew B. Blaschko:
On the Relationship Between Calibrated Predictors and Unbiased Volume Estimation. 678-688 - Federico Turella, Gustav Bredell, Alexander Okupnik, Sebastiano Caprara, Dimitri Graf, Reto Sutter, Ender Konukoglu:
High-Resolution Segmentation of Lumbar Vertebrae from Conventional Thick Slice MRI. 689-698 - Jun Wei, Yiwen Hu, Ruimao Zhang, Zhen Li, S. Kevin Zhou, Shuguang Cui:
Shallow Attention Network for Polyp Segmentation. 699-708 - Heiko Maier, Shahrooz Faghihroohi, Nassir Navab:
A Line to Align: Deep Dynamic Time Warping for Retinal OCT Segmentation. 709-719 - Mengjun Cheng, Zishang Kong, Guoli Song, Yonghong Tian, Yongsheng Liang, Jie Chen:
Learnable Oriented-Derivative Network for Polyp Segmentation. 720-730 - Yanglan Ou, Ye Yuan, Xiaolei Huang, Kelvin K. Wong, John Volpi, James Z. Wang, Stephen T. C. Wong:
LambdaUNet: 2.5D Stroke Lesion Segmentation of Diffusion-Weighted MR Images. 731-741
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