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ORCID25th MICCAI 2022: Singapore - Part I
- 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 I. Lecture Notes in Computer Science 13431, Springer 2022, ISBN 978-3-031-16430-9
Brain Development and Atlases
- Benoît Sauty, Stanley Durrleman:
Progression Models for Imaging Data with Longitudinal Variational Auto Encoders. 3-13 - Feng Chang, Chaoyi Wu, Yanfeng Wang, Ya Zhang, Xin Chen, Qi Tian:
Boundary-Enhanced Self-supervised Learning for Brain Structure Segmentation. 14-23 - Minhui Yu, Hao Guan, Yuqi Fang, Ling Yue, Mingxia Liu:
Domain-Prior-Induced Structural MRI Adaptation for Clinical Progression Prediction of Subjective Cognitive Decline. 24-33 - Shengjie Zhang, Xiang Chen, Bohan Ren, Haibo Yang, Ziqi Yu, Xiao-Yong Zhang, Yuan Zhou:
3D Global Fourier Network for Alzheimer's Disease Diagnosis Using Structural MRI. 34-43 - Ignacio Sarasua, Sebastian Pölsterl, Christian Wachinger:
CASHformer: Cognition Aware SHape Transformer for Longitudinal Analysis. 44-54 - Huy-Dung Nguyen, Michaël Clément, Boris Mansencal, Pierrick Coupé:
Interpretable Differential Diagnosis for Alzheimer's Disease and Frontotemporal Dementia. 55-65 - Marla Narazani, Ignacio Sarasua, Sebastian Pölsterl, Aldana Lizarraga, Igor Yakushev, Christian Wachinger:
Is a PET All You Need? A Multi-modal Study for Alzheimer's Disease Using 3D CNNs. 66-76 - Joël Chavas, Louise Guillon, Marco Pascucci, Benoit Dufumier, Denis Rivière, Jean-François Mangin:
Unsupervised Representation Learning of Cingulate Cortical Folding Patterns. 77-87 - Eike Petersen, Aasa Feragen, Maria Luise da Costa Zemsch, Anders Henriksen, Oskar Eiler Wiese Christensen, Melanie Ganz:
Feature Robustness and Sex Differences in Medical Imaging: A Case Study in MRI-Based Alzheimer's Disease Detection. 88-98 - Feng Liu, Guihong Wan, Yevgeniy R. Semenov, Patrick L. Purdon:
Extended Electrophysiological Source Imaging with Spatial Graph Filters. 99-109
DWI and Tractography
- Geng Chen, Haotian Jiang, Jiannan Liu, Jiquan Ma, Hui Cui, Yong Xia, Pew-Thian Yap:
Hybrid Graph Transformer for Tissue Microstructure Estimation with Undersampled Diffusion MRI Data. 113-122 - Davood Karimi, Ali Gholipour:
Atlas-Powered Deep Learning (ADL) - Application to Diffusion Weighted MRI. 123-132 - Wan Liu, Qi Lu, Zhizheng Zhuo, Yaou Liu, Chuyang Ye:
One-Shot Segmentation of Novel White Matter Tracts via Extensive Data Augmentation. 133-142 - Zhenwei Wang, Yifan Lv, Mengshen He, Enjie Ge, Ning Qiang, Bao Ge:
Accurate Corresponding Fiber Tract Segmentation via FiberGeoMap Learner. 143-152 - Tianshu Zheng, Weihao Zheng, Yi Sun, Yi Zhang, Chuyang Ye, Dan Wu:
An Adaptive Network with Extragradient for Diffusion MRI-Based Microstructure Estimation. 153-162 - Claire Cury, Jean-Marie Batail, Julie Coloigner:
Shape-Based Features of White Matter Fiber-Tracts Associated with Outcome in Major Depression Disorder. 163-173 - Yuqian Chen, Fan Zhang, Chaoyi Zhang, Tengfei Xue, Leo R. Zekelman, Jianzhong He, Yang Song, Nikos Makris, Yogesh Rathi, Alexandra J. Golby, Weidong Cai, Lauren J. O'Donnell:
White Matter Tracts are Point Clouds: Neuropsychological Score Prediction and Critical Region Localization via Geometric Deep Learning. 174-184 - Logiraj Kumaralingam, Thanikasalam Kokul, Sittampalam Sotheeswaran, Jeyasuthan Mahadevan, Nagulan Ratnarajah:
Segmentation of Whole-Brain Tractography: A Deep Learning Algorithm Based on 3D Raw Curve Points. 185-195 - Fan Zhang, Tengfei Xue, Weidong Cai, Yogesh Rathi, Carl-Fredrik Westin, Lauren J. O'Donnell:
TractoFormer: A Novel Fiber-Level Whole Brain Tractography Analysis Framework Using Spectral Embedding and Vision Transformers. 196-206 - Julio E. Villalon-Reina, Clara Moreau, Talia M. Nir, Neda Jahanshad, Anne M. Maillard, David Romascano, Bogdan Draganski, Sarah Lippé, Carrie E. Bearden, Seyed Mostafa Kia, Andre F. Marquand, Sébastien Jacquemont, Paul M. Thompson:
Multi-site Normative Modeling of Diffusion Tensor Imaging Metrics Using Hierarchical Bayesian Regression. 207-217
Functional Brain Networks
- Xuesong Wang, Lina Yao, Islem Rekik, Yu Zhang:
Contrastive Functional Connectivity Graph Learning for Population-based fMRI Classification. 221-230 - Yueting Li, Qingyue Wei, Ehsan Adeli, Kilian M. Pohl, Qingyu Zhao:
Joint Graph Convolution for Analyzing Brain Structural and Functional Connectome. 231-240 - Shijie Zhao, Long Fang, Lin Wu, Yang Yang, Junwei Han:
Decoding Task Sub-type States with Group Deep Bidirectional Recurrent Neural Network. 241-250 - Tianji Pang, Dajiang Zhu, Tianming Liu, Junwei Han, Shijie Zhao:
Hierarchical Brain Networks Decomposition via Prior Knowledge Guided Deep Belief Network. 251-260 - Antoine Grigis, Chloé Gomez, Vincent Frouin, Lynn Uhrig, Béchir Jarraya:
Interpretable Signature of Consciousness in Resting-State Functional Network Brain Activity. 261-270 - Kai-Cheng Chuang, Sreekrishna Ramakrishnapillai, Lydia Bazzano, Owen T. Carmichael:
Nonlinear Conditional Time-Varying Granger Causality of Task fMRI via Deep Stacking Networks and Adaptive Convolutional Kernels. 271-281 - Rotem Leibovitz, Jhonathan Osin, Lior Wolf, Guy Gurevitch, Talma Hendler:
fMRI Neurofeedback Learning Patterns are Predictive of Personal and Clinical Traits. 282-294 - Mengshen He, Xiangyu Hou, Zhenwei Wang, Zili Kang, Xin Zhang, Ning Qiang, Bao Ge:
Multi-head Attention-Based Masked Sequence Model for Mapping Functional Brain Networks. 295-304 - Fatih Said Duran, Abdurrahman Beyaz, Islem Rekik:
Dual-HINet: Dual Hierarchical Integration Network of Multigraphs for Connectional Brain Template Learning. 305-314 - Naresh Nandakumar, Komal Manzoor, Shruti Agarwal, Haris I. Sair, Archana Venkataraman:
RefineNet: An Automated Framework to Generate Task and Subject-Specific Brain Parcellations for Resting-State fMRI Analysis. 315-325 - Sixtus Dakurah, D. Vijay Anand, Zijian Chen, Moo K. Chung:
Modelling Cycles in Brain Networks with the Hodge Laplacian. 326-335 - Chongyue Zhao, Liang Zhan, Paul M. Thompson, Heng Huang:
Predicting Spatio-Temporal Human Brain Response Using fMRI. 336-345 - Chongyue Zhao, Liang Zhan, Paul M. Thompson, Heng Huang:
Revealing Continuous Brain Dynamical Organization with Multimodal Graph Transformer. 346-355 - Chongyue Zhao, Liang Zhan, Paul M. Thompson, Heng Huang:
Explainable Contrastive Multiview Graph Representation of Brain, Mind, and Behavior. 356-365 - Lin Zhao, Zihao Wu, Haixing Dai, Zhengliang Liu, Tuo Zhang, Dajiang Zhu, Tianming Liu:
Embedding Human Brain Function via Transformer. 366-375 - Injun Choi, Guorong Wu, Won Hwa Kim:
How Much to Aggregate: Learning Adaptive Node-Wise Scales on Graphs for Brain Networks. 376-385 - Javid Dadashkarimi, Amin Karbasi, Dustin Scheinost:
Combining Multiple Atlases to Estimate Data-Driven Mappings Between Functional Connectomes Using Optimal Transport. 386-395 - Wei Dai, Stephanie Noble, Dustin Scheinost:
The Semi-constrained Network-Based Statistic (scNBS): Integrating Local and Global Information for Brain Network Inference. 396-405 - Carlo Amodeo, Igor Fortel, Olusola Ajilore, Liang Zhan, Alex D. Leow, Theja Tulabandhula:
Unified Embeddings of Structural and Functional Connectome via a Function-Constrained Structural Graph Variational Auto-Encoder. 406-415
Neuroimaging
- Chloé Gomez, Antoine Grigis, Lynn Uhrig, Béchir Jarraya:
Characterization of Brain Activity Patterns Across States of Consciousness Based on Variational Auto-Encoders. 419-429 - Ana Lawry Aguila, James Chapman, Mohammed Janahi, André Altmann:
Conditional VAEs for Confound Removal and Normative Modelling of Neurodegenerative Diseases. 430-440 - Yi Hao Chan, Wei Chee Yew, Jagath C. Rajapakse:
Semi-supervised Learning with Data Harmonisation for Biomarker Discovery from Resting State fMRI. 441-451 - Jun-Ho Kim, Mohammed A. Al-masni, Seul Lee, Haejoon Lee, Dong-Hyun Kim:
Cerebral Microbleeds Detection Using a 3D Feature Fused Region Proposal Network with Hard Sample Prototype Learning. 452-460 - Mehmet Saygin Seyfioglu, Zixuan Liu, Pranav Kamath, Sadjyot Gangolli, Sheng Wang, Thomas J. Grabowski, Linda G. Shapiro:
Brain-Aware Replacements for Supervised Contrastive Learning in Detection of Alzheimer's Disease. 461-470
Heart and Lung Imaging
- Jia Guo, Xinglong Liu, Yinan Chen, Shaoting Zhang, Guangyu Tao, Hong Yu, Huiyuan Zhu, Wenhui Lei, Huiqi Li, Na Wang:
AANet: Artery-Aware Network for Pulmonary Embolism Detection in CTPA Images. 473-483 - Jiansheng Fang, Jingwen Wang, Anwei Li, Yuguang Yan, Yonghe Hou, Chao Song, Hongbo Liu, Jiang Liu:
Siamese Encoder-based Spatial-Temporal Mixer for Growth Trend Prediction of Lung Nodules on CT Scans. 484-494 - Kaiming Kuang, Li Zhang, Jingyu Li, Hongwei Li, Jiajun Chen, Bo Du, Jiancheng Yang:
What Makes for Automatic Reconstruction of Pulmonary Segments. 495-505 - Minghui Zhang, Hanxiao Zhang, Guang-Zhong Yang, Yun Gu:
CFDA: Collaborative Feature Disentanglement and Augmentation for Pulmonary Airway Tree Modeling of COVID-19 CTs. 506-516 - Zheyao Gao, Lei Li, Fuping Wu, Sihan Wang, Xiahai Zhuang:
Decoupling Predictions in Distributed Learning for Multi-center Left Atrial MRI Segmentation. 517-527 - Xiangde Luo, Minhao Hu, Wenjun Liao, Shuwei Zhai, Tao Song, Guotai Wang, Shaoting Zhang:
Scribble-Supervised Medical Image Segmentation via Dual-Branch Network and Dynamically Mixed Pseudo Labels Supervision. 528-538 - Boah Kim, Jong Chul Ye:
Diffusion Deformable Model for 4D Temporal Medical Image Generation. 539-548 - Yuqiang Gao, Guanyu Yang, Xiaoming Qi, Yinsu Zhu, Shuo Li:
SAPJNet: Sequence-Adaptive Prototype-Joint Network for Small Sample Multi-sequence MRI Diagnosis. 549-559 - Xin He, Guohao Ying, Jiyong Zhang, Xiaowen Chu:
Evolutionary Multi-objective Architecture Search Framework: Application to COVID-19 3D CT Classification. 560-570 - Kavitha Vimalesvaran, Fatmatülzehra Uslu, Sameer Zaman, Christoforos Galazis, James Howard, Graham Cole, Anil A. Bharath:
Detecting Aortic Valve Pathology from the 3-Chamber Cine Cardiac MRI View. 571-580 - Gaurang Karwande, Amarachi Mbakawe, Joy T. Wu, Leo A. Celi, Mehdi Moradi, Ismini Lourentzou:
CheXRelNet: An Anatomy-Aware Model for Tracking Longitudinal Relationships Between Chest X-Rays. 581-591 - Gabriel Bernardino, Anders Jonsson, Filip Loncaric, Pablo-Miki Martí Castellote, Marta Sitges, Patrick Clarysse, Nicolas Duchateau:
Reinforcement Learning for Active Modality Selection During Diagnosis. 592-601 - Pooneh R. Tabrizi, Holger R. Roth, Alison Tompsett, Athelia Rosa Paulli, Kelsey Brown, Joselyn Rwebembera, Emmy Okello, Andrea Z. Beaton, Craig Sable, Marius George Linguraru:
Ensembled Prediction of Rheumatic Heart Disease from Ungated Doppler Echocardiography Acquired in Low-Resource Settings. 602-612 - Seong-A Park, Hyung-Chul Lee, Chul-Woo Jung, Hyun-Lim Yang:
Attention Mechanisms for Physiological Signal Deep Learning: Which Attention Should We Take? 613-622 - Chengwei Pan, Gangming Zhao, Junjie Fang, Baolian Qi, Jiaheng Liu, Chaowei Fang, Dingwen Zhang, Jinpeng Li, Yizhou Yu:
Computer-Aided Tuberculosis Diagnosis with Attribute Reasoning Assistance. 623-633 - Abdullah-Al-Zubaer Imran, Sen Wang, Debashish Pal, Sandeep Dutta, Evan Zucker, Adam S. Wang:
Multimodal Contrastive Learning for Prospective Personalized Estimation of CT Organ Dose. 634-643 - Yiting Lu, Jun Fu, Xin Li, Wei Zhou, Sen Liu, Xinxin Zhang, Wei Wu, Congfu Jia, Ying Liu, Zhibo Chen:
RTN: Reinforced Transformer Network for Coronary CT Angiography Vessel-level Image Quality Assessment. 644-653 - Sontje Ihler, Felix Kuhnke, Svenja Spindeldreier:
A Comprehensive Study of Modern Architectures and Regularization Approaches on CheXpert5000. 654-663 - Rui Xu, Yong Luo, Bo Du, Kaiming Kuang, Jiancheng Yang:
LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule Detection. 664-674 - Shafa Balaram, Cuong Manh Nguyen, Ashraf Kassim, Pavitra Krishnaswamy:
Consistency-Based Semi-supervised Evidential Active Learning for Diagnostic Radiograph Classification. 675-685 - Kunlei Hong, Lin Guo, Yuan Ming Fleming Lure:
Self-Rating Curriculum Learning for Localization and Segmentation of Tuberculosis on Chest Radiograph. 686-695 - Yihua Sun, Qingsong Yao, Yuanyuan Lyu, Jianji Wang, Yi Xiao, Hongen Liao, S. Kevin Zhou:
Rib Suppression in Digital Chest Tomosynthesis. 696-706 - Chen-Han Tsai, Yu-Shao Peng:
Multi-task Lung Nodule Detection in Chest Radiographs with a Dual Head Network. 707-717
Dermatology
- Suraj Mishra, Yizhe Zhang, Li Zhang, Tianyu Zhang, X. Sharon Hu, Danny Z. Chen:
Data-Driven Deep Supervision for Skin Lesion Classification. 721-731 - Deval Mehta, Yaniv Gal, Adrian Bowling, C. Paul Bonnington, Zongyuan Ge:
Out-of-Distribution Detection for Long-Tailed and Fine-Grained Skin Lesion Images. 732-742 - Yawen Wu, Dewen Zeng, Xiaowei Xu, Yiyu Shi, Jingtong Hu:
FairPrune: Achieving Fairness Through Pruning for Dermatological Disease Diagnosis. 743-753 - Wenlong Hang, Yecheng Huang, Shuang Liang, Baiying Lei, Kup-Sze Choi, Jing Qin:
Reliability-Aware Contrastive Self-ensembling for Semi-supervised Medical Image Classification. 754-763
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