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Graph Learning in Medical Imaging

First International Workshop, GLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. Daoqiang Zhang

    1. Nanjing University of Aeronautics and Astronautics, Nanjing, China

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  2. Luping Zhou

    1. University of Sydney, Sydney, Australia

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  3. Biao Jie

    1. Anhui Normal University, Wuhu, China

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  4. Mingxia Liu

    1. University of North Carolina at Chapel Hill, Chapel Hill, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11849)

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

Included in the following conference series:

Conference proceedings info: GLMI 2019.

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Table of contents (21 papers)

  1. Front Matter

    Pages i-ix
    Download chapter PDF

  2. Graph Hyperalignment for Multi-subject fMRI Functional Alignment

    • Weida Li, Fang Chen, Daoqiang Zhang
    Pages 1-8

  3. Interactive 3D Segmentation Editing and Refinement via Gated Graph Neural Networks

    • Xiaosong Wang, Ling Zhang, Holger Roth, Daguang Xu, Ziyue Xu
    Pages 9-17

  4. Adaptive Thresholding of Functional Connectivity Networks for fMRI-Based Brain Disease Analysis

    • Zhengdong Wang, Biao Jie, Weixin Bian, Daoqiang Zhang, Dinggang Shen, Mingxia Liu
    Pages 18-26

  5. Graph-Kernel-Based Multi-task Structured Feature Selection on Multi-level Functional Connectivity Networks for Brain Disease Classification

    • Zhengdong Wang, Biao Jie, Mi Wang, Chunxiang Feng, Wen Zhou, Dinggang Shen et al.
    Pages 27-35

  6. Linking Convolutional Neural Networks with Graph Convolutional Networks: Application in Pulmonary Artery-Vein Separation

    • Zhiwei Zhai, Marius Staring, Xuhui Zhou, Qiuxia Xie, Xiaojuan Xiao, M. Els Bakker et al.
    Pages 36-43

  7. Comparative Analysis of Magnetic Resonance Fingerprinting Dictionaries via Dimensionality Reduction

    • Oleh Dzyubachyk, Kirsten Koolstra, Nicola Pezzotti, Boudewijn P. F. Lelieveldt, Andrew Webb, Peter Börnert
    Pages 44-52

  8. Learning Deformable Point Set Registration with Regularized Dynamic Graph CNNs for Large Lung Motion in COPD Patients

    • Lasse Hansen, Doris Dittmer, Mattias P. Heinrich
    Pages 53-61

  9. Graph Convolutional Networks for Coronary Artery Segmentation in Cardiac CT Angiography

    • Jelmer M. Wolterink, Tim Leiner, Ivana Išgum
    Pages 62-69

  10. Triplet Graph Convolutional Network for Multi-scale Analysis of Functional Connectivity Using Functional MRI

    • Dongren Yao, Mingxia Liu, Mingliang Wang, Chunfeng Lian, Jie Wei, Li Sun et al.
    Pages 70-78

  11. Multi-scale Graph Convolutional Network for Mild Cognitive Impairment Detection

    • Shuangzhi Yu, Guanghui Yue, Ahmed Elazab, Xuegang Song, Tianfu Wang, Baiying Lei
    Pages 79-87

  12. DeepBundle: Fiber Bundle Parcellation with Graph Convolution Neural Networks

    • Feihong Liu, Jun Feng, Geng Chen, Ye Wu, Yoonmi Hong, Pew-Thian Yap et al.
    Pages 88-95

  13. Identification of Functional Connectivity Features in Depression Subtypes Using a Data-Driven Approach

    • Xingjuan Li, Samantha Burnham, Jurgen Fripp, Yu Li, Xue Li, Amir Fazlollahi et al.
    Pages 96-103

  14. Movie-Watching fMRI Reveals Inter-subject Synchrony Alteration in Functional Brain Activity in ADHD

    • Chao Tang, Ziyi Huang, Senyu Zhou, Qi Wang, Fa Yi, Jingxin Nie
    Pages 104-111

  15. Weakly- and Semi-supervised Graph CNN for Identifying Basal Cell Carcinoma on Pathological Images

    • Junyan Wu, Jia-Xing Zhong, Eric Z. Chen, Jingwei Zhang, Jay J. Ye, Limin Yu
    Pages 112-119

  16. Geometric Brain Surface Network for Brain Cortical Parcellation

    • Wen Zhang, Yalin Wang
    Pages 120-129

  17. Automatic Detection of Craniomaxillofacial Anatomical Landmarks on CBCT Images Using 3D Mask R-CNN

    • Yankun Lang, Li Wang, Pew-Thian Yap, Chunfeng Lian, Hannah Deng, Kim-Han Thung et al.
    Pages 130-137

  18. Discriminative-Region-Aware Residual Network for Adolescent Brain Structure and Cognitive Development Analysis

    • Yongsheng Pan, Mingxia Liu, Li Wang, Yong Xia, Dinggang Shen
    Pages 138-146

  19. Graph Modeling for Identifying Breast Tumor Located in Dense Background of a Mammogram

    • Shelda Sajeev, Mariusz Bajger, Gobert Lee
    Pages 147-154

  20. OCD Diagnosis via Smoothing Sparse Network and Stacked Sparse Auto-Encoder Learning

    • Peng Yang, Lili Jin, Chuangyong Xu, Tianfu Wang, Baiying Lei, Ziwen Peng
    Pages 155-163
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  1. Graph Learning in Medical Imaging

Keywords

About this book

This book constitutes the refereed proceedings of the First International Workshop on Graph Learning in Medical Imaging, GLMI 2019, held in conjunction with MICCAI 2019 in Shenzhen, China, in October 2019.

The 21 full papers presented were carefully reviewed and selected from 42 submissions. The papers focus on major trends and challenges of graph learning in medical imaging and present original work aimed to identify new cutting-edge techniques and their applications in medical imaging.

Editors and Affiliations

  • Nanjing University of Aeronautics and Astronautics, Nanjing, China

    Daoqiang Zhang

  • University of Sydney, Sydney, Australia

    Luping Zhou

  • Anhui Normal University, Wuhu, China

    Biao Jie

  • University of North Carolina at Chapel Hill, Chapel Hill, USA

    Mingxia Liu

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