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ORCID23rd MICCAI 2020: Lima, Peru - Part VII
- 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 VII. Lecture Notes in Computer Science 12267, Springer 2020, ISBN 978-3-030-59727-6
Brain Development and Atlases
- Maryam Ghanbari, Li-Ming Hsu, Zhen Zhou, Amir Ghanbari, Zhanhao Mo, Pew-Thian Yap, Han Zhang, Dinggang Shen:
A New Metric for Characterizing Dynamic Redundancy of Dense Brain Chronnectome and Its Application to Early Detection of Alzheimer's Disease. 3-12 - Mayssa Soussia, Xuyun Wen, Zhen Zhou, Bing Jin, Tae-Eui Kam, Li-Ming Hsu, Zhengwang Wu, Gang Li, Li Wang, Islem Rekik, Weili Lin, Dinggang Shen, Han Zhang:
A Computational Framework for Dissociating Development-Related from Individually Variable Flexibility in Regional Modularity Assignment in Early Infancy. 13-21 - Tao Zhong, Yu Zhang, Fenqiang Zhao, Yuchen Pei, Lufan Liao, Zhenyuan Ning, Li Wang, Dinggang Shen, Gang Li:
Domain-Invariant Prior Knowledge Guided Attention Networks for Robust Skull Stripping of Developing Macaque Brains. 22-32 - Nandinee Fariah Haq, Jiayue Cai, Tianze Yu, Martin J. McKeown, Z. Jane Wang:
Parkinson's Disease Detection from fMRI-Derived Brainstem Regional Functional Connectivity Networks. 33-43 - Jin Li, Chenyuan Bian, Dandan Chen, Xianglian Meng, Haoran Luo, Hong Liang, Li Shen:
Persistent Feature Analysis of Multimodal Brain Networks Using Generalized Fused Lasso for EMCI Identification. 44-52 - Lu Zhang, Li Wang, Dajiang Zhu:
Recovering Brain Structural Connectivity from Functional Connectivity via Multi-GCN Based Generative Adversarial Network. 53-61 - Gia H. Ngo, Meenakshi Khosla, Keith Jamison, Amy Kuceyeski, Mert R. Sabuncu:
From Connectomic to Task-Evoked Fingerprints: Individualized Prediction of Task Contrasts from Resting-State Functional Connectivity. 62-71 - Dan Hu, Fan Wang, Han Zhang, Zhengwang Wu, Li Wang, Weili Lin, Gang Li, Dinggang Shen:
Disentangled Intensive Triplet Autoencoder for Infant Functional Connectome Fingerprinting. 72-82 - Fan Yang, Amal Isaiah, Won Hwa Kim:
COVLET: Covariance-Based Wavelet-Like Transform for Statistical Analysis of Brain Characteristics in Children. 83-93 - Tuo Zhang, Zhibin He, Xi Jiang, Lei Guo, Xiaoping Hu, Tianming Liu, Lei Du:
Species-Shared and -Specific Structural Connections Revealed by Dirty Multi-task Regression. 94-103 - Nina Cheng, Alejandro Frangi, Zhiguo Zhang, Denao Deng, Lihua Zhao, Tianfu Wang, Yichen Wei, Bihan Yu, Wei Mai, Gaoxiong Duan, Xiucheng Nong, Chong Li, Jiahui Su, Baiying Lei:
Self-weighted Multi-task Learning for Subjective Cognitive Decline Diagnosis. 104-113 - Jing Yang, Qi Zhu, Rui Zhang, Jiashuang Huang, Daoqiang Zhang:
Unified Brain Network with Functional and Structural Data. 114-123 - Xuegang Song, Alejandro F. Frangi, Xiaohua Xiao, Jiuwen Cao, Tianfu Wang, Baiying Lei:
Integrating Similarity Awareness and Adaptive Calibration in Graph Convolution Network to Predict Disease. 124-133 - Xin Zhang, Jiale Cheng, Hao Ni, Chenyang Li, Xiangmin Xu, Zhengwang Wu, Li Wang, Weili Lin, Dinggang Shen, Gang Li:
Infant Cognitive Scores Prediction with Multi-stream Attention-Based Temporal Path Signature Features. 134-144 - Dongang Wang, Chenyu Wang, Lynette Masters, Michael Barnett:
Masked Multi-Task Network for Case-Level Intracranial Hemorrhage Classification in Brain CT Volumes. 145-154 - Mustafa Burak Gurbuz, Islem Rekik:
Deep Graph Normalizer: A Geometric Deep Learning Approach for Estimating Connectional Brain Templates. 155-165 - Islem Mhiri, Mohamed Ali Mahjoub, Islem Rekik:
Supervised Multi-topology Network Cross-Diffusion for Population-Driven Brain Network Atlas Estimation. 166-176 - Benjamin Billot, Eleanor D. Robinson, Adrian V. Dalca, Juan Eugenio Iglesias:
Partial Volume Segmentation of Brain MRI Scans of Any Resolution and Contrast. 177-187 - Yu Zhang, Bo Liu, Yinuo Wang, Zhengzhou Gao, Xiangzhi Bai, Fugen Zhou:
BDB-Net: Boundary-Enhanced Dual Branch Network for Whole Brain Segmentation. 188-197 - Ziyang Liu, Jian Cheng, Haogang Zhu, Jicong Zhang, Tao Liu:
Brain Age Estimation from MRI Using a Two-Stage Cascade Network with Ranking Loss. 198-207 - Shen Wang, Kongming Liang, Yiming Li, Yizhou Yu, Yizhou Wang:
Context-Aware Refinement Network Incorporating Structural Connectivity Prior for Brain Midline Delineation. 208-217 - Yanshuai Tu, Duyan Ta, Zhonglin Lu, Yalin Wang:
Optimizing Visual Cortex Parameterization with Error-Tolerant Teichmüller Map in Retinotopic Mapping. 218-227 - Shuangzhi Yu, Shuqiang Wang, Xiaohua Xiao, Jiuwen Cao, Guanghui Yue, Dongdong Liu, Tianfu Wang, Yanwu Xu, Baiying Lei:
Multi-scale Enhanced Graph Convolutional Network for Early Mild Cognitive Impairment Detection. 228-237 - Ying Huang, Fan Wang, Zhengwang Wu, Zengsi Chen, Han Zhang, Li Wang, Weili Lin, Dinggang Shen, Gang Li:
Construction of Spatiotemporal Infant Cortical Surface Functional Templates. 238-248
DWI and Tractography
- Ye Wu, Yoonmi Hong, Sahar Ahmad, Weili Lin, Dinggang Shen, Pew-Thian Yap:
Tract Dictionary Learning for Fast and Robust Recognition of Fiber Bundles. 251-259 - Ye Wu, Yoonmi Hong, Sahar Ahmad, Wei-Tang Chang, Weili Lin, Dinggang Shen, Pew-Thian Yap:
Globally Optimized Super-Resolution of Diffusion MRI Data via Fiber Continuity. 260-269 - Qi Lu, Yuxing Li, Chuyang Ye:
White Matter Tract Segmentation with Self-supervised Learning. 270-279 - Geng Chen, Yoonmi Hong, Yongqin Zhang, Jaeil Kim, Khoi Minh Huynh, Jiquan Ma, Weili Lin, Dinggang Shen, Pew-Thian Yap:
Estimating Tissue Microstructure with Undersampled Diffusion Data via Graph Convolutional Neural Networks. 280-290 - Pietro Astolfi, Ruben S. Verhagen, Laurent Petit, Emanuele Olivetti, Jonathan Masci, Davide Boscaini, Paolo Avesani:
Tractogram Filtering of Anatomically Non-plausible Fibers with Geometric Deep Learning. 291-301 - Yuchuan Qiao, Yonggang Shi:
Unsupervised Deep Learning for Susceptibility Distortion Correction in Connectome Imaging. 302-310 - Heejong Kim, Sungmin Hong, Martin Styner, Joseph Piven, Kelly N. Botteron, Guido Gerig:
Hierarchical Geodesic Modeling on the Diffusion Orientation Distribution Function for Longitudinal DW-MRI Analysis. 311-321 - Daniel Haehn, Loraine Franke, Fan Zhang, Suheyla Cetin Karayumak, Steve Pieper, Lauren J. O'Donnell, Yogesh Rathi:
TRAKO: Efficient Transmission of Tractography Data for Visualization. 322-332 - Aydan Gasimova, Gavin Seegoolam, Liang Chen, Paul Bentley, Daniel Rueckert:
Spatial Semantic-Preserving Latent Space Learning for Accelerated DWI Diagnostic Report Generation. 333-342 - Anuja Sharma, Guido Gerig:
Trajectories from Distribution-Valued Functional Curves: A Unified Wasserstein Framework. 343-353 - Khoi Minh Huynh, Ye Wu, Kim-Han Thung, Sahar Ahmad, Hoyt Patrick Taylor IV, Dinggang Shen, Pew-Thian Yap:
Characterizing Intra-soma Diffusion with Spherical Mean Spectrum Imaging. 354-363
Functional Brain Networks
- Jiazhou Chen, Guoqiang Han, Hongmin Cai, Junbo Ma, Minjeong Kim, Paul J. Laurienti, Guorong Wu:
Estimating Common Harmonic Waves of Brain Networks on Stiefel Manifold. 367-376 - Qing Li, Wei Zhang, Jinglei Lv, Xia Wu, Tianming Liu:
Neural Architecture Search for Optimization of Spatial-Temporal Brain Network Decomposition. 377-386 - Junbo Ma, Xiaofeng Zhu, Defu Yang, Jiazhou Chen, Guorong Wu:
Attention-Guided Deep Graph Neural Network for Longitudinal Alzheimer's Disease Analysis. 387-396 - Eunjin Jeon, Eunsong Kang, Jiyeon Lee, Jaein Lee, Tae-Eui Kam, Heung-Il Suk:
Enriched Representation Learning in Resting-State fMRI for Early MCI Diagnosis. 397-406 - Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Noah Lewis, Zening Fu, Vince D. Calhoun, Sergey M. Plis:
Whole MILC: Generalizing Learned Dynamics Across Tasks, Datasets, and Populations. 407-417 - Tzu-An Song, Samadrita Roy Chowdhury, Fan Yang, Heidi I. L. Jacobs, Jorge Sepulcre, Van J. Wedeen, Keith A. Johnson, Joyita Dutta:
A Physics-Informed Geometric Learning Model for Pathological Tau Spread in Alzheimer's Disease. 418-427 - Roza G. Bayrak, Jorge Alberto Salas, Yuankai Huo, Catie Chang:
A Deep Pattern Recognition Approach for Inferring Respiratory Volume Fluctuations from fMRI Data. 428-436 - Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti, Nicholas F. Wymbs, Joshua Robinson, Stewart Mostofsky, Archana Venkataraman:
A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism. 437-447 - Siyuan Gao, Gal Mishne, Dustin Scheinost:
Poincaré Embedding Reveals Edge-Based Functional Networks of the Brain. 448-457 - Stephanie Noble, Dustin Scheinost:
The Constrained Network-Based Statistic: A New Level of Inference for Neuroimaging. 458-468 - Jhonathan Osin, Lior Wolf, Guy Gurevitch, Nimrod Jakob Keynan, Tom Fruchtman-Steinbok, Ayelet Or-Borichev, Talma Hendler:
Learning Personal Representations from fMRI by Predicting Neurofeedback Performance. 469-478 - Chongyue Zhao, Hongming Li, Zhicheng Jiao, Tianming Du, Yong Fan:
A 3D Convolutional Encapsulated Long Short-Term Memory (3DConv-LSTM) Model for Denoising fMRI Data. 479-488 - Yi Lin, Jia Hou, Paul J. Laurienti, Guorong Wu:
Detecting Changes of Functional Connectivity by Dynamic Graph Embedding Learning. 489-497 - Qinglin Dong, Ning Qiang, Jinglei Lv, Xiang Li, Tianming Liu, Quanzheng Li:
Discovering Functional Brain Networks with 3D Residual Autoencoder (ResAE). 498-507 - Qinglin Dong, Ning Qiang, Jinglei Lv, Xiang Li, Tianming Liu, Quanzheng Li:
Spatiotemporal Attention Autoencoder (STAAE) for ADHD Classification. 508-517 - David S. Lee, Ashish Sahib, Katherine L. Narr, Elvis Nunez, Shantanu H. Joshi:
Global Diffeomorphic Phase Alignment of Time-Series from Resting-State fMRI Data. 518-527 - Soham Gadgil, Qingyu Zhao, Adolf Pfefferbaum, Edith V. Sullivan, Ehsan Adeli, Kilian M. Pohl:
Spatio-Temporal Graph Convolution for Resting-State fMRI Analysis. 528-538 - Meenakshi Khosla, Gia H. Ngo, Keith Jamison, Amy Kuceyeski, Mert R. Sabuncu:
A Shared Neural Encoding Model for the Prediction of Subject-Specific fMRI Response. 539-548
Neuroimaging
- Alaa Bessadok, Mohamed Ali Mahjoub, Islem Rekik:
Topology-Aware Generative Adversarial Network for Joint Prediction of Multiple Brain Graphs from a Single Brain Graph. 551-561 - Yongxiang Huang, Albert C. S. Chung:
Edge-Variational Graph Convolutional Networks for Uncertainty-Aware Disease Prediction. 562-572 - Rena Elkin, Saad Nadeem, Hedok Lee, Helene Benveniste, Allen R. Tannenbaum:
Fisher-Rao Regularized Transport Analysis of the Glymphatic System and Waste Drainage. 573-582 - Yunbi Liu, Yongsheng Pan, Wei Yang, Zhenyuan Ning, Ling Yue, Mingxia Liu, Dinggang Shen:
Joint Neuroimage Synthesis and Representation Learning for Conversion Prediction of Subjective Cognitive Decline. 583-592 - Ezequiel de la Rosa, David Robben, Diana Maria Sima, Jan S. Kirschke, Bjoern H. Menze:
Differentiable Deconvolution for Improved Stroke Perfusion Analysis. 593-602 - Peng Yang, Qiong Yang, Wei Zheng, Li Shen, Tianfu Wang, Ziwen Peng, Baiying Lei:
Spatial Similarity-Aware Learning and Fused Deep Polynomial Network for Detection of Obsessive-Compulsive Disorder. 603-612 - Wen Zhang, Liang Zhan, Paul M. Thompson, Yalin Wang:
Deep Representation Learning for Multimodal Brain Networks. 613-624 - Xiaoxiao Li, Yuan Zhou, Nicha C. Dvornek, Muhan Zhang, Juntang Zhuang, Pamela Ventola, James S. Duncan:
Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis. 625-635 - Kilian Hett, Rémi Giraud, Hans J. Johnson, Jane S. Paulsen, Jeffrey D. Long, Ipek Oguz:
Patch-Based Abnormality Maps for Improved Deep Learning-Based Classification of Huntington's Disease. 636-645 - Liangjun Chen, Zhengwang Wu, Dan Hu, Ya Wang, Zhanhao Mo, Li Wang, Weili Lin, Dinggang Shen, Gang Li:
A Deep Spatial Context Guided Framework for Infant Brain Subcortical Segmentation. 646-656 - Anna Volokitin, Ertunc Erdil, Neerav Karani, Kerem Can Tezcan, Xiaoran Chen, Luc Van Gool, Ender Konukoglu:
Modelling the Distribution of 3D Brain MRI Using a 2D Slice VAE. 657-666 - Samuel Gerber, Marc Niethammer:
Spatial Component Analysis to Mitigate Multiple Testing in Voxel-Based Analysis. 667-677 - Junhao Wen, Erdem Varol, Ganesh B. Chand, Aristeidis Sotiras, Christos Davatzikos:
MAGIC: Multi-scale Heterogeneity Analysis and Clustering for Brain Diseases. 678-687 - Peirong Liu, Yueh Z. Lee, Stephen R. Aylward, Marc Niethammer:
PIANO: Perfusion Imaging via Advection-Diffusion. 688-698 - Seyed Mostafa Kia, Hester Huijsdens, Richard Dinga, Thomas Wolfers, Maarten Mennes, Ole A. Andreassen, Lars T. Westlye, Christian F. Beckmann, Andre F. Marquand:
Hierarchical Bayesian Regression for Multi-site Normative Modeling of Neuroimaging Data. 699-709 - Robert Robinson, Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Marius de Groot, Ronald M. Summers, Daniel Rueckert, Ben Glocker:
Image-Level Harmonization of Multi-site Data Using Image-and-Spatial Transformer Networks. 710-719 - Blake E. Dewey, Lianrui Zuo, Aaron Carass, Yufan He, Yihao Liu, Ellen M. Mowry, Scott D. Newsome, Jiwon Oh, Peter A. Calabresi, Jerry L. Prince:
A Disentangled Latent Space for Cross-Site MRI Harmonization. 720-729 - Patrick J. Bolan, Francesca Branzoli, Anna Luisa Di Stefano, Lucia Nichelli, Romain Valabrègue, Sara L. Saunders, Mehmet Akçakaya, Marc Sanson, Stéphane Lehéricy, Malgorzata Marjanska:
Automated Acquisition Planning for Magnetic Resonance Spectroscopy in Brain Cancer. 730-739
Positron Emission Tomography
- Bo Zhou, Yu-Jung Tsai, Chi Liu:
Simultaneous Denoising and Motion Estimation for Low-Dose Gated PET Using a Siamese Adversarial Network with Gate-to-Gate Consistency Learning. 743-752 - Zhuotun Zhu, Dakai Jin, Ke Yan, Tsung-Ying Ho, Xianghua Ye, Dazhou Guo, Chun-Hung Chao, Jing Xiao, Alan L. Yuille, Le Lu:
Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-Based Gating Using 3D CT/PET Imaging in Radiotherapy. 753-762 - Yige Peng, Lei Bi, Michael J. Fulham, Dagan Feng, Jinman Kim:
Multi-modality Information Fusion for Radiomics-Based Neural Architecture Search. 763-771 - Chun-Hung Chao, Zhuotun Zhu, Dazhou Guo, Ke Yan, Tsung-Ying Ho, Jinzheng Cai, Adam P. Harrison, Xianghua Ye, Jing Xiao, Alan L. Yuille, Min Sun, Le Lu, Dakai Jin:
Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network. 772-782 - Qiupeng Feng, Huafeng Liu:
Rethinking PET Image Reconstruction: Ultra-Low-Dose, Sinogram and Deep Learning. 783-792 - Nuobei Xie, Kuang Gong, Ning Guo, ZhiXing Qin, Jianan Cui, Zhifang Wu, Huafeng Liu, Quanzheng Li:
Clinically Translatable Direct Patlak Reconstruction from Dynamic PET with Motion Correction Using Convolutional Neural Network. 793-802 - Yifan Zheng, Yoonsuk Huh, Qianqian Su, Jiaming Wang, Yunduan Lin, Kai Vetter, Youngho Seo:
Collimatorless Scintigraphy for Imaging Extremely Low Activity Targeted Alpha Therapy (TAT) with Weighted Robust Least Squares (WRLS). 803-811
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