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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

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. Dajiang Zhu

    1. The University of Texas at Arlington, Arlington, USA

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  2. Jingwen Yan

    1. Indiana University – Purdue University Indianapolis, Indianapolis, USA

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  3. Heng Huang

    1. University of Pittsburgh, Pittsburgh, USA

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  4. Li Shen

    1. University of Pennsylvania, Philadelphia, USA

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  5. Paul M. Thompson

    1. University of Southern California, Marina Del Rey, USA

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  6. Carl-Fredrik Westin

    1. Harvard Medical School, Boston, USA

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  7. Xavier Pennec

    1. Inria Sophia-Antipolis, Sophia-Antipolis, France

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  8. Sarang Joshi

    1. University of Utah, Salt Lake City, USA

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  9. Mads Nielsen

    1. University of Copenhagen, Copenhagen, Denmark

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  10. Tom Fletcher

    1. University of Virginia, Charlottesville, USA

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  11. Stanley Durrleman

    1. Inria, Paris, France

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  12. Stefan Sommer

    1. University of Copenhagen, Copenhagen, Denmark

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11846)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: MBIA 2019, MFCA 2019.

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Table of contents (23 papers)

  1. Front Matter

    Pages i-xvii
    Download chapter PDF

  2. MBIA

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. 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

    3. An Edge Enhanced SRGAN for MRI Super Resolution in Slice-Selection Direction

      • Jia Liu, Fang Chen, Xianyu Wang, Hongen Liao
      Pages 12-20

    4. Exploring Functional Connectivity Biomarker in Autism Using Group-Wise Sparse Representation

      • Yudan Ren, Shuai Wang
      Pages 21-29

    5. 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

    6. Mapping the Spatio-Temporal Functional Coherence in the Resting Brain

      • Ze Wang
      Pages 39-48

    7. Species-Preserved Structural Connections Revealed by Sparse Tensor CCA

      • Zhibin He, Ying Huang, Tianming Liu, Lei Guo, Lei Du, Tuo Zhang
      Pages 49-56

    8. 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

    9. 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

    10. 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

    11. Biological Knowledge Guided Deep Neural Network for Brain Genotype-Phenotype Association Study

      • Yanfu Zhang, Liang Zhan, Paul M. Thompson, Heng Huang
      Pages 84-92

    12. 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

    13. 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

    14. 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

    15. Structural Similarity Based Anatomical and Functional Brain Imaging Fusion

      • Nishant Kumar, Nico Hoffmann, Martin Oelschlägel, Edmund Koch, Matthias Kirsch, Stefan Gumhold
      Pages 121-129

    16. Multimodal Brain Tumor Segmentation Using Encoder-Decoder with Hierarchical Separable Convolution

      • Zhongdao Jia, Zhimin Yuan, Jialin Peng
      Pages 130-138

    17. 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

  3. MFCA

    1. Front Matter

      Pages 149-149
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    2. 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
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  1. Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy

Keywords

About this book

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.

Editors and Affiliations

  • The University of Texas at Arlington, Arlington, USA

    Dajiang Zhu

  • Indiana University – Purdue University Indianapolis, Indianapolis, USA

    Jingwen Yan

  • University of Pittsburgh, Pittsburgh, USA

    Heng Huang

  • University of Pennsylvania, Philadelphia, USA

    Li Shen

  • University of Southern California, Marina Del Rey, USA

    Paul M. Thompson

  • Harvard Medical School, Boston, USA

    Carl-Fredrik Westin

  • Inria Sophia-Antipolis, Sophia-Antipolis, France

    Xavier Pennec

  • University of Utah, Salt Lake City, USA

    Sarang Joshi

  • University of Copenhagen, Copenhagen, Denmark

    Mads Nielsen, Stefan Sommer

  • University of Virginia, Charlottesville, USA

    Tom Fletcher

  • Inria, Paris, France

    Stanley Durrleman

Bibliographic Information

  • Book Title: Multimodal Brain Image Analysis and Mathematical Foundations of Computational Anatomy

  • Book Subtitle: 4th International Workshop, MBIA 2019, and 7th International Workshop, MFCA 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings

  • Editors: 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

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-030-33226-6

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer Nature Switzerland AG 2019

  • Softcover ISBN: 978-3-030-33225-9Published: 11 October 2019

  • eBook ISBN: 978-3-030-33226-6Published: 10 October 2019

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XVII, 230

  • Number of Illustrations: 22 b/w illustrations, 91 illustrations in colour

  • Topics: Pattern Recognition, Image Processing and Computer Vision, Artificial Intelligence, Information Systems and Communication Service

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