ENGLISH

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

Book information

Publisher
Springer International Publishing
Year
2019
ISBN
978-3-030-33225-9, 978-3-030-33226-6
Language
english
Format
PDF
Filesize
35 MB (36315105 bytes)
Series
Lecture Notes in Computer Science 11846
Edition
1st ed. 2019
Pages
XVII, 230\241
Time added
2020-02-08 04:42:03

Description

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. Front Matter ....Pages i-xvii Front Matter ....Pages 1-1 Non-rigid Registration of White Matter Tractography Using Coherent Point Drift Algorithm (Wenjuan Wang, Jin Liu, Tengfei Wang, Zongtao Hu, Li Xia, Hongzhi Wang et al.)....Pages 3-11 An Edge Enhanced SRGAN for MRI Super Resolution in Slice-Selection Direction (Jia Liu, Fang Chen, Xianyu Wang, Hongen Liao)....Pages 12-20 Exploring Functional Connectivity Biomarker in Autism Using Group-Wise Sparse Representation (Yudan Ren, Shuai Wang)....Pages 21-29 Classifying Stages of Mild Cognitive Impairment via Augmented Graph Embedding (Haoteng Tang, Lei Guo, Emily Dennis, Paul M. Thompson, Heng Huang, Olusola Ajilore et al.)....Pages 30-38 Mapping the Spatio-Temporal Functional Coherence in the Resting Brain (Ze Wang)....Pages 39-48 Species-Preserved Structural Connections Revealed by Sparse Tensor CCA (Zhibin He, Ying Huang, Tianming Liu, Lei Guo, Lei Du, Tuo Zhang)....Pages 49-56 Identification of Abnormal Cortical 3-Hinge Folding Patterns on Autism Spectral Brains (Ying Huang, Zhibin He, Tianming Liu, Lei Guo, Tuo Zhang)....Pages 57-65 Exploring Brain Hemodynamic Response Patterns via Deep Recurrent Autoencoder (Shijie Zhao, Yan Cui, Yaowu Chen, Xin Zhang, Wei Zhang, Huan Liu et al.)....Pages 66-74 3D Convolutional Long-Short Term Memory Network for Spatiotemporal Modeling of fMRI Data (Wei Suo, Xintao Hu, Bowei Yan, Mengyang Sun, Lei Guo, Junwei Han et al.)....Pages 75-83 Biological Knowledge Guided Deep Neural Network for Brain Genotype-Phenotype Association Study (Yanfu Zhang, Liang Zhan, Paul M. Thompson, Heng Huang)....Pages 84-92 Learning Human Cognition via fMRI Analysis Using 3D CNN and Graph Neural Network (Xiuyan Ni, Tian Gao, Tingting Wu, Jin Fan, Chao Chen)....Pages 93-101 CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation (Hongying Liu, Xiongjie Shen, Fanhua Shang, Feihang Ge, Fei Wang)....Pages 102-111 BrainPainter: A Software for the Visualisation of Brain Structures, Biomarkers and Associated Pathological Processes (Răzvan V. Marinescu, Arman Eshaghi, Daniel C. Alexander, Polina Golland)....Pages 112-120 Structural Similarity Based Anatomical and Functional Brain Imaging Fusion (Nishant Kumar, Nico Hoffmann, Martin Oelschlägel, Edmund Koch, Matthias Kirsch, Stefan Gumhold)....Pages 121-129 Multimodal Brain Tumor Segmentation Using Encoder-Decoder with Hierarchical Separable Convolution (Zhongdao Jia, Zhimin Yuan, Jialin Peng)....Pages 130-138 Prioritizing Amyloid Imaging Biomarkers in Alzheimer’s Disease via Learning to Rank (Bo Peng, Zhiyun Ren, Xiaohui Yao, Kefei Liu, Andrew J. Saykin, Li Shen et al.)....Pages 139-148 Front Matter ....Pages 149-149 Diffeomorphic Metric Learning and Template Optimization for Registration-Based Predictive Models (Ayagoz Mussabayeva, Maxim Pisov, Anvar Kurmukov, Alexey Kroshnin, Yulia Denisova, Li Shen et al.)....Pages 151-161 3D Mapping of Serial Histology Sections with Anomalies Using a Novel Robust Deformable Registration Algorithm (Daniel Tward, Xu Li, Bingxing Huo, Brian Lee, Partha Mitra, Michael Miller)....Pages 162-173 Spatiotemporal Modeling for Image Time Series with Appearance Change: Application to Early Brain Development (James Fishbaugh, Martin Styner, Karen Grewen, John Gilmore, Guido Gerig)....Pages 174-185 Surface Foliation Based Brain Morphometry Analysis (Chengfeng Wen, Na Lei, Ming Ma, Xin Qi, Wen Zhang, Yalin Wang et al.)....Pages 186-195 Mixture Probabilistic Principal Geodesic Analysis (Youshan Zhang, Jiarui Xing, Miaomiao Zhang)....Pages 196-208 A Geodesic Mixed Effects Model in Kendall’s Shape Space (Esfandiar Nava-Yazdani, Hans-Christian Hege, Christoph von Tycowicz)....Pages 209-218 An As-Invariant-As-Possible \(\text {GL}^+(3){}\)-Based Statistical Shape Model (Felix Ambellan, Stefan Zachow, Christoph von Tycowicz)....Pages 219-228 Back Matter ....Pages 229-230

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