Title Multimodal brain image analysis and mathematical foundations of computational anatomy : 4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, held in conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings / Dajiang Zhu, Jingwen Yan, Heng Huang, Li Shen, Paul M. Thompson, Carl-Fredrik Westin, Xavier Pennec, Sarang Joshi, Mads Nielsen, Tom Fletcher, Stanley Durrleman, Stefan Sommer (eds.)

Published Cham, Switzerland : Springer, 2019

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Description 1 online resource (xvii, 230 pages) : illustrations (some color) Series Lecture notes in computer science ; 11846 LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics Lecture notes in computer science ; 11846. LNCS sublibrary. SL 6, Image processing, computer vision, pattern recognition, and graphics. Contents Intro; Additional Workshop Editors; Preface; Multimodal Brain Image Analysis (MBIA); Organization; Preface; Organization; Contents; MBIA; Non-rigid Registration of White Matter Tractography Using Coherent Point Drift Algorithm; Abstract; 1 Introduction; 2 Methods; 2.1 Overview and Preprocessing; 2.2 Clustering and Central Fiber Extracting; 2.3 Non-rigid Registration; 3 Experiment and Results; 3.1 Registration Based on CPD; 3.2 Evaluation Based on Distance Between Fiber Tracts; 3.3 Evaluation Based on FA Profile Along the Fiber Tracts; 4 Conclusion; Acknowledgements; References An Edge Enhanced SRGAN for MRI Super Resolution in Slice-Selection DirectionAbstract; 1 Introduction; 2 Method; 2.1 Two-Stage Super-Resolution Generator Network; 2.2 Discriminator Network; 2.3 Edge Enhanced Hybrid Loss Function; 3 Experiment and Result; 3.1 Dataset and Training Detail; 3.2 Results; 4 Conclusion; References; Exploring Functional Connectivity Biomarker in Autism Using Group-Wise Sparse Representation; Abstract; 1 Introduction; 2 Materials and Methods; 2.1 Overview; 2.2 Data Acquisition and Pre-Processing; 2.3 Sparse Representation Theory 2.4 Sparse Representation of Whole-Brain FMRI Data2.5 Functional Connectivity Analysis; 3 Result; 3.1 Node Identification on Simulated Data; 3.2 Node Identification on ASD Data; 3.3 Functional Connectivity Biomarkers; 3.4 Classification Performance; 3.5 Anatomical Locations of Network Nodes; 4 Conclusion; References; Classifying Stages of Mild Cognitive Impairment via Augmented Graph Embedding; Abstract; 1 Introduction; 2 Method; 2.1 Feature Preparation; 2.2 Feature Embedding; 2.3 Feature Augmentation; 3 Experiment; 3.1 Data Description, Preprocessing and Network Reconstruction 3.2 Experimental Settings3.3 Comparison to Other Baseline Methods; 4 Conclusion; References; Mapping the Spatio-Temporal Functional Coherence in the Resting Brain; Abstract; 1 Introduction; 2 Method; 2.1 A New Multivariate SampEn and Spatio-Temporal Coherence Mapping (STCM); 2.2 Evaluations with Numerical Simulations; 2.3 Evaluations with rsfMRI Data from Human Connectome Project (HCP); 3 Results; 3.1 Numerical Simulation Results; 3.2 Mean STIC Map and Test-Retest Stability of STIC; 3.3 Sex Effects on STIC; 3.4 Age Effects on STIC; 4 Discussion and Conclusion; Acknowledgement; References Species-Preserved Structural Connections Revealed by Sparse Tensor CCAAbstract; 1 Introduction; 2 Materials and Methods; 2.1 Datasets; 2.2 Data Preprocessing; 2.3 Structural Connective Connectome Construction; 2.4 Sparse Tensor Canonical Correlation Analysis (STCCA); 3 Results; 3.1 Cross-Validation; 3.2 DTI Tracts Comparison Between Human and Macaque; 4 Conclusion; References; Identification of Abnormal Cortical 3-Hinge Folding Patterns on Autism Spectral Brains; Abstract; 1 Introduction; 2 Materials and Methods; 2.1 Datasets and Preprocessing; 2.2 3-Hinges Detection Summary This book constitutes the refereed joint proceedings of the 4th International Workshop on Multimodal Brain Image Analysis, MBAI 2019, and the 7th International Workshop on Mathematical Foundations of Computational Anatomy, MFCA 2019, held in conjunction with the 22nd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2019, in Shenzhen, China, in October 2019. The 16 full papers presented at MBAI 2019 and the 7 full papers presented at MFCA 2019 were carefully reviewed and selected. The MBAI papers intend to move forward the state of the art in multimodal brain image analysis, in terms of analysis methodologies, algorithms, software systems, validation approaches, benchmark datasets, neuroscience, and clinical applications. The MFCA papers are devoted to statistical and geometrical methods for modeling the variability of biological shapes. The goal is to foster the interactions between the mathematical community around shapes and the MICCAI community around computational anatomy applications Notes International conference proceedings Includes author index Online resource; title from PDF title page (SpringerLink, viewed October 16, 2019) Subject Brain -- Imaging -- Data processing -- Congresses Image analysis -- Congresses Image analysis Genre/Form Electronic books proceedings (reports) Conference papers and proceedings Conference papers and proceedings. Actes de congrès. Form Electronic book Author Zhu, Dajiang, editor Yan, Jingwen, editor Huang, Heng, editor Shen, Li, editor Thompson, Paul M., editor Westin, Carl-Fredrik, editor Pennec, Xavier, 1970- editor. Joshi, Sarang, editor Nielsen, Mads, editor. Fletcher, Tom (Computer scientist), editor. Durrleman, Stanley, editor. Sommer, Stefan, editor MFCA (Workshop) (7th : 2019 : Shenzhen Shi, China), jointly held conference. International Conference on Medical Image Computing and Computer-Assisted Intervention (22nd : 2019 : Shenzhen Shi, China), jointly held conference. ISBN 9783030332266 3030332268

Other Titles MBIA 2019 MFCA 2019

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