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25th MICCAI 2022: Singapore - Part V
- Linwei Wang, Qi Dou, P. Thomas Fletcher, Stefanie Speidel, Shuo Li:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2022 - 25th International Conference, Singapore, September 18-22, 2022, Proceedings, Part V. Lecture Notes in Computer Science 13435, Springer 2022, ISBN 978-3-031-16442-2
Image Segmentation II
- Raja Ebsim, Benjamin G. Faber, Fiona C. Saunders, Monika Frysz, Jennifer S. Gregory, Nicholas C. Harvey, Jonathan H. Tobias, Claudia Lindner, Timothy F. Cootes:
Automatic Segmentation of Hip Osteophytes in DXA Scans Using U-Nets. 3-12 - Wookjin Choi, Navdeep Dahiya, Saad Nadeem:
CIRDataset: A Large-Scale Dataset for Clinically-Interpretable Lung Nodule Radiomics and Malignancy Prediction. 13-22 - Jeya Maria Jose Valanarasu, Vishal M. Patel:
UNeXt: MLP-Based Rapid Medical Image Segmentation Network. 23-33 - Yicheng Wu, Zhonghua Wu, Qianyi Wu, Zongyuan Ge, Jianfei Cai:
Exploring Smoothness and Class-Separation for Semi-supervised Medical Image Segmentation. 34-43 - Han Yang, Lu Shen, Mengke Zhang, Qiuli Wang:
Uncertainty-Guided Lung Nodule Segmentation with Feature-Aware Attention. 44-54 - Dazhou Guo, Jia Ge, Ke Yan, Puyang Wang, Zhuotun Zhu, Dandan Zheng, Xian-Sheng Hua, Le Lu, Tsung-Ying Ho, Xianghua Ye, Dakai Jin:
Thoracic Lymph Node Segmentation in CT Imaging via Lymph Node Station Stratification and Size Encoding. 55-65 - Xiaofeng Liu, Fangxu Xing, Nadya Shusharina, Ruth Lim, C.-C. Jay Kuo, Georges El Fakhri, Jonghye Woo:
ACT: Semi-supervised Domain-Adaptive Medical Image Segmentation with Asymmetric Co-training. 66-76 - Zewen Liu, Timothy F. Cootes:
A Sense of Direction in Biomedical Neural Networks. 77-86 - Dong Zhang, Raymond Confidence, Udunna Anazodo:
Stroke Lesion Segmentation from Low-Quality and Few-Shot MRIs via Similarity-Weighted Self-ensembling Framework. 87-96 - Yifan Liu, Jie Liu, Yixuan Yuan:
Edge-Oriented Point-Cloud Transformer for 3D Intracranial Aneurysm Segmentation. 97-106 - Yao Zhang, Nanjun He, Jiawei Yang, Yuexiang Li, Dong Wei, Yawen Huang, Yang Zhang, Zhiqiang He, Yefeng Zheng:
mmFormer: Multimodal Medical Transformer for Incomplete Multimodal Learning of Brain Tumor Segmentation. 107-117 - Huabing Liu, Dong Ni, Dinggang Shen, Jinda Wang, Zhenyu Tang:
Multimodal Brain Tumor Segmentation Using Contrastive Learning Based Feature Comparison with Monomodal Normal Brain Images. 118-127 - Ziyuan Zhao, Fangcheng Zhou, Zeng Zeng, Cuntai Guan, S. Kevin Zhou:
Meta-hallucinator: Towards Few-Shot Cross-Modality Cardiac Image Segmentation. 128-139 - Zhaohu Xing, Lequan Yu, Liang Wan, Tong Han, Lei Zhu:
NestedFormer: Nested Modality-Aware Transformer for Brain Tumor Segmentation. 140-150 - Chen Chen, Zeju Li, Cheng Ouyang, Matthew Sinclair, Wenjia Bai, Daniel Rueckert:
MaxStyle: Adversarial Style Composition for Robust Medical Image Segmentation. 151-161 - Himashi Peiris, Munawar Hayat, Zhaolin Chen, Gary F. Egan, Mehrtash Harandi:
A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation. 162-172 - Yizhe Zhang, Suraj Mishra, Peixian Liang, Hao Zheng, Danny Z. Chen:
Usable Region Estimate for Assessing Practical Usability of Medical Image Segmentation Models. 173-182 - Zechen Zhao, Heran Yang, Jian Sun:
Modality-Adaptive Feature Interaction for Brain Tumor Segmentation with Missing Modalities. 183-192 - Dong Liang, Jun Liu, Kuanquan Wang, Gongning Luo, Wei Wang, Shuo Li:
Position-Prior Clustering-Based Self-attention Module for Knee Cartilage Segmentation. 193-202 - Junjia Huang, Haofeng Li, Guanbin Li, Xiang Wan:
Attentive Symmetric Autoencoder for Brain MRI Segmentation. 203-213 - Zhe Xu, Donghuan Lu, Yixin Wang, Jie Luo, Dong Wei, Yefeng Zheng, Raymond Kai-Yu Tong:
Denoising for Relaxing: Unsupervised Domain Adaptive Fundus Image Segmentation Without Source Data. 214-224 - Yu Fang, Zhiming Cui, Lei Ma, Lanzhuju Mei, Bojun Zhang, Yue Zhao, Zhihao Jiang, Yiqiang Zhan, Yongsheng Pan, Min Zhu, Dinggang Shen:
Curvature-Enhanced Implicit Function Network for High-quality Tooth Model Generation from CBCT Images. 225-234 - Wentao Liu, Tong Tian, Weijin Xu, Huihua Yang, Xipeng Pan, Songlin Yan, Lemeng Wang:
PHTrans: Parallelly Aggregating Global and Local Representations for Medical Image Segmentation. 235-244 - Meng Jia, Matthew Kyan:
Learning Tumor-Induced Deformations to Improve Tumor-Bearing Brain MR Segmentation. 245-255 - Xiaoming Qi, Guanyu Yang, Yuting He, Wangyan Liu, Ali Islam, Shuo Li:
Contrastive Re-localization and History Distillation in Federated CMR Segmentation. 256-265 - Chenchu Xu, Dong Zhang, Yuhui Song, Leonardo Kayat Bittencourt, Sree Harsha Tirumani, Shuo Li:
Contrast-Free Liver Tumor Detection Using Ternary Knowledge Transferred Teacher-Student Deep Reinforcement Learning. 266-275 - Negin Ghamsarian, Mario Taschwer, Raphael Sznitman, Klaus Schoeffmann:
DeepPyramid: Enabling Pyramid View and Deformable Pyramid Reception for Semantic Segmentation in Cataract Surgery Videos. 276-286 - Weiyuan Lin, Hui Liu, Lin Gu, Zhifan Gao:
A Geometry-Constrained Deformable Attention Network for Aortic Segmentation. 287-296 - Ailiang Lin, Jiayu Xu, Jinxing Li, Guangming Lu:
ConTrans: Improving Transformer with Convolutional Attention for Medical Image Segmentation. 297-307 - Tal Shaharabany, Lior Wolf:
End-to-End Segmentation of Medical Images via Patch-Wise Polygons Prediction. 308-318 - Edward G. A. Henderson, Andrew F. Green, Marcel van Herk, Eliana M. Vasquez Osorio:
Automatic Identification of Segmentation Errors for Radiotherapy Using Geometric Learning. 319-329 - Jieun Lee, Kwanseok Oh, Dinggang Shen, Heung-Il Suk:
A Novel Knowledge Keeper Network for 7T-Free but 7T-Guided Brain Tissue Segmentation. 330-339 - Savinien Bonheur, Franz Thaler, Michael Pienn, Horst Olschewski, Horst Bischof, Martin Urschler:
OnlyCaps-Net, a Capsule only Based Neural Network for 2D and 3D Semantic Segmentation. 340-349 - Leonie Henschel, David Kügler, Derek S. Andrews, Christine Wu Nordahl, Martin Reuter:
Identifying and Combating Bias in Segmentation Networks by Leveraging Multiple Resolutions. 350-359 - Shangqi Gao, Hangqi Zhou, Yibo Gao, Xiahai Zhuang:
Joint Modeling of Image and Label Statistics for Enhancing Model Generalizability of Medical Image Segmentation. 360-369 - Xiaowu Sun, Li-Hsin Cheng, Sven Plein, Pankaj Garg, Rob J. van der Geest:
Transformer Based Feature Fusion for Left Ventricle Segmentation in 4D Flow MRI. 370-379 - Jingyang Zhang, Peng Xue, Ran Gu, Yuning Gu, Mianxin Liu, Yongsheng Pan, Zhiming Cui, Jiawei Huang, Lei Ma, Dinggang Shen:
Learning Towards Synchronous Network Memorizability and Generalizability for Continual Segmentation Across Multiple Sites. 380-390 - Xiao Zhang, Jingyang Zhang, Lei Ma, Peng Xue, Yan Hu, Dijia Wu, Yiqiang Zhan, Jun Feng, Dinggang Shen:
Progressive Deep Segmentation of Coronary Artery via Hierarchical Topology Learning. 391-400 - Ling Huang, Thierry Denoeux, Pierre Vera, Su Ruan:
Evidence Fusion with Contextual Discounting for Multi-modality Medical Image Segmentation. 401-411 - Aimon Rahman, Wele Gedara Chaminda Bandara, Jeya Maria Jose Valanarasu, Ilker Hacihaliloglu, Vishal M. Patel:
Orientation-Guided Graph Convolutional Network for Bone Surface Segmentation. 412-421 - Udaranga Wickramasinghe, Patrick M. Jensen, Mian Shah, Jiancheng Yang, Pascal Fua:
Weakly Supervised Volumetric Image Segmentation with Deformed Templates. 422-432 - Muhammad Osama Khan, Yi Fang:
Implicit Neural Representations for Medical Imaging Segmentation. 433-443 - Han Liu, Yubo Fan, Hao Li, Jiacheng Wang, Dewei Hu, Can Cui, Ho Hin Lee, Huahong Zhang, Ipek Oguz:
ModDrop++: A Dynamic Filter Network with Intra-subject Co-training for Multiple Sclerosis Lesion Segmentation with Missing Modalities. 444-453 - Skylar E. Stolte, Kyle Volle, Aprinda Indahlastari, Alejandro Albizu, Adam J. Woods, Kevin M. Brink, Matthew Hale, Ruogu Fang:
DOMINO: Domain-Aware Model Calibration in Medical Image Segmentation. 454-463 - Qin Liu, Zhenlin Xu, Yining Jiao, Marc Niethammer:
iSegFormer: Interactive Segmentation via Transformers with Application to 3D Knee MR Images. 464-474 - Yanglan Ou, Ye Yuan, Xiaolei Huang, Stephen T. C. Wong, John Volpi, James Z. Wang, Kelvin K. Wong:
Patcher: Patch Transformers with Mixture of Experts for Precise Medical Image Segmentation. 475-484 - Di Liu, Yunhe Gao, Qilong Zhangli, Ligong Han, Xiaoxiao He, Zhaoyang Xia, Song Wen, Qi Chang, Zhennan Yan, Mu Zhou, Dimitris N. Metaxas:
TransFusion: Multi-view Divergent Fusion for Medical Image Segmentation with Transformers. 485-495 - Rodrigo Santa Cruz, Léo Lebrat, Darren Fu, Pierrick Bourgeat, Jurgen Fripp, Clinton Fookes, Olivier Salvado:
CorticalFlow++: Boosting Cortical Surface Reconstruction Accuracy, Regularity, and Interoperability. 496-505 - Raghavendra Selvan, Nikhil Bhagwat, Lasse F. Wolff Anthony, Benjamin Kanding, Erik B. Dam:
Carbon Footprint of Selecting and Training Deep Learning Models for Medical Image Analysis. 506-516 - Ziheng Wang, Xiongkuo Min, Fangyu Shi, Ruinian Jin, Saida S. Nawrin, Ichen Yu, Ryoichi Nagatomi:
SMESwin Unet: Merging CNN and Transformer for Medical Image Segmentation. 517-526 - Sofie Tilborghs, Jeroen Bertels, David Robben, Dirk Vandermeulen, Frederik Maes:
The Dice Loss in the Context of Missing or Empty Labels: Introducing $\varPhi $ and ε. 527-537 - Benjamin Billot, Colin G. Magdamo, Steven E. Arnold, Sudeshna Das, Juan Eugenio Iglesias:
Robust Segmentation of Brain MRI in the Wild with Hierarchical CNNs and No Retraining. 538-548 - Seung Yeon Shin, Ronald M. Summers:
Deep Reinforcement Learning for Small Bowel Path Tracking Using Different Types of Annotations. 549-559 - Yufan He, Dong Yang, Andriy Myronenko, Daguang Xu:
Efficient Population Based Hyperparameter Scheduling for Medical Image Segmentation. 560-569 - Jiazhen Zhang, Rajesh Venkataraman, Lawrence H. Staib, John A. Onofrey:
Atlas-Based Semantic Segmentation of Prostate Zones. 570-579 - Mou-Cheng Xu, Yukun Zhou, Chen Jin, Marius de Groot, Daniel C. Alexander, Neil P. Oxtoby, Yipeng Hu, Joseph Jacob:
Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi-supervised Segmentation. 580-590 - Doruk Öner, Hussein Osman, Mateusz Kozinski, Pascal Fua:
Enforcing Connectivity of 3D Linear Structures Using Their 2D Projections. 591-601 - Qing Lu, Xiaowei Xu, Shunjie Dong, Cong Hao, Lei Yang, Cheng Zhuo, Yiyu Shi:
RT-DNAS: Real-Time Constrained Differentiable Neural Architecture Search for 3D Cardiac Cine MRI Segmentation. 602-612
Integration of Imaging with Non-imaging Biomarkers
- Jinghan Sun, Dong Wei, Liansheng Wang, Yefeng Zheng:
Lesion Guided Explainable Few Weak-Shot Medical Report Generation. 615-625 - Can Cui, Han Liu, Quan Liu, Ruining Deng, Zuhayr Asad, Yaohong Wang, Shilin Zhao, Haichun Yang, Bennett A. Landman, Yuankai Huo:
Survival Prediction of Brain Cancer with Incomplete Radiology, Pathology, Genomic, and Demographic Data. 626-635 - Xiaohan Xing, Zhen Chen, Meilu Zhu, Yuenan Hou, Zhifan Gao, Yixuan Yuan:
Discrepancy and Gradient-Guided Multi-modal Knowledge Distillation for Pathological Glioma Grading. 636-646 - Philip Müller, Georgios Kaissis, Congyu Zou, Daniel Rueckert:
Radiological Reports Improve Pre-training for Localized Imaging Tasks on Chest X-Rays. 647-657 - Ke Yu, Shantanu Ghosh, Zhexiong Liu, Christopher Deible, Kayhan Batmanghelich:
Anatomy-Guided Weakly-Supervised Abnormality Localization in Chest X-rays. 658-668 - Xi Chen, Wenwen Zeng, Guoqing Wu, Yu Lei, Wei Ni, Yuanyuan Wang, Yuxiang Gu, Jinhua Yu:
Identification of Vascular Cognitive Impairment in Adult Moyamoya Disease via Integrated Graph Convolutional Network. 669-678 - Zhihong Chen, Yuhao Du, Jinpeng Hu, Yang Liu, Guanbin Li, Xiang Wan, Tsung-Hui Chang:
Multi-modal Masked Autoencoders for Medical Vision-and-Language Pre-training. 679-689 - Constantin Seibold, Simon Reiß, M. Saquib Sarfraz, Rainer Stiefelhagen, Jens Kleesiek:
Breaking with Fixed Set Pathology Recognition Through Report-Guided Contrastive Training. 690-700 - Maxime Kayser, Cornelius Emde, Oana-Maria Camburu, Guy Parsons, Bartlomiej W. Papiez, Thomas Lukasiewicz:
Explaining Chest X-Ray Pathologies in Natural Language. 701-713 - Ajay Kumar Tanwani, Joelle K. Barral, Daniel Freedman:
RepsNet: Combining Vision with Language for Automated Medical Reports. 714-724 - Masoud Monajatipoor, Mozhdeh Rouhsedaghat, Liunian Harold Li, C.-C. Jay Kuo, Aichi Chien, Kai-Wei Chang:
BERTHop: An Effective Vision-and-Language Model for Chest X-ray Disease Diagnosis. 725-734
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