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Machine Learning in Medical Imaging

9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings

  • Conference proceedings
  • © 2018

Overview

Editors:
  1. Yinghuan Shi

    1. Nanjing University, Nanjing, China

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  2. Heung-Il Suk

    1. 617A, Science Library, Korea University, Seoul, Korea (Republic of)

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    You can also search for this editor in PubMed   Google Scholar

  3. Mingxia Liu

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

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11046)

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

Included in the following conference series:

Conference proceedings info: MLMI 2018.

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Table of contents (47 papers)

  1. Front Matter

    Pages I-XII
    Download chapter PDF

  2. Developing Novel Weighted Correlation Kernels for Convolutional Neural Networks to Extract Hierarchical Functional Connectivities from fMRI for Disease Diagnosis

    • Biao Jie, Mingxia Liu, Chunfeng Lian, Feng Shi, Dinggang Shen
    Pages 1-9

  3. Robust Contextual Bandit via the Capped-\(\ell _{2}\) Norm for Mobile Health Intervention

    • Feiyun Zhu, Xinliang Zhu, Sheng Wang, Jiawen Yao, Zhichun Xiao, Junzhou Huang
    Pages 10-18

  4. Dynamic Multi-scale CNN Forest Learning for Automatic Cervical Cancer Segmentation

    • Nesrine Bnouni, Islem Rekik, Mohamed Salah Rhim, Najoua Essoukri Ben Amara
    Pages 19-27

  5. Multi-task Fundus Image Quality Assessment via Transfer Learning and Landmarks Detection

    • Yaxin Shen, Ruogu Fang, Bin Sheng, Ling Dai, Huating Li, Jing Qin et al.
    Pages 28-36

  6. End-to-End Lung Nodule Detection in Computed Tomography

    • Dufan Wu, Kyungsang Kim, Bin Dong, Georges El Fakhri, Quanzheng Li
    Pages 37-45

  7. CT Image Enhancement Using Stacked Generative Adversarial Networks and Transfer Learning for Lesion Segmentation Improvement

    • Youbao Tang, Jinzheng Cai, Le Lu, Adam P. Harrison, Ke Yan, Jing Xiao et al.
    Pages 46-54

  8. Deep Learning Based Inter-modality Image Registration Supervised by Intra-modality Similarity

    • Xiaohuan Cao, Jianhuan Yang, Li Wang, Zhong Xue, Qian Wang, Dinggang Shen
    Pages 55-63

  9. Regional Abnormality Representation Learning in Structural MRI for AD/MCI Diagnosis

    • Jun-Sik Choi, Eunho Lee, Heung-Il Suk
    Pages 64-72

  10. Joint Registration And Segmentation Of Xray Images Using Generative Adversarial Networks

    • Dwarikanath Mahapatra, Zongyuan Ge, Suman Sedai, Rajib Chakravorty
    Pages 73-80

  11. SCCA-Ref: Novel Sparse Canonical Correlation Analysis with Reference to Discover Independent Spatial Associations Between White Matter Hyperintensities and Atrophy

    • Gerard Sanroma, Loes Rutten-Jacobs, Valerie Lohner, Johanna Kramme, Sach Mukherjee, Martin Reuter et al.
    Pages 81-88

  12. Synthesizing Dynamic MRI Using Long-Term Recurrent Convolutional Networks

    • Frank Preiswerk, Cheng-Chieh Cheng, Jie Luo, Bruno Madore
    Pages 89-97

  13. Automatically Designing CNN Architectures for Medical Image Segmentation

    • Aliasghar Mortazi, Ulas Bagci
    Pages 98-106

  14. Rotation Invariance and Directional Sensitivity: Spherical Harmonics versus Radiomics Features

    • Adrien Depeursinge, Julien Fageot, Vincent Andrearczyk, John Paul Ward, Michael Unser
    Pages 107-115

  15. Can Dilated Convolutions Capture Ultrasound Video Dynamics?

    • Mohammad Ali Maraci, Weidi Xie, J. Alison Noble
    Pages 116-124

  16. Topological Correction of Infant Cortical Surfaces Using Anatomically Constrained U-Net

    • Liang Sun, Daoqiang Zhang, Li Wang, Wei Shao, Zengsi Chen, Weili Lin et al.
    Pages 125-133

  17. Self-taught Learning with Residual Sparse Autoencoders for HEp-2 Cell Staining Pattern Recognition

    • Xian-Hua Han, JiandDe Sun, Lanfen Lin, Yen-Wei Chen
    Pages 134-142

  18. Semantic-Aware Generative Adversarial Nets for Unsupervised Domain Adaptation in Chest X-Ray Segmentation

    • Cheng Chen, Qi Dou, Hao Chen, Pheng-Ann Heng
    Pages 143-151

  19. Brain Status Prediction with Non-negative Projective Dictionary Learning

    • Mingli Zhang, Christian Desrosiers, Yuhong Guo, Caiming Zhang, Budhachandra Khundrakpam, Alan Evans
    Pages 152-160

  20. Classification of Pancreatic Cystic Neoplasms Based on Multimodality Images

    • Weixiang Chen, Hongchen Ji, Jianjiang Feng, Rong Liu, Yi Yu, Ruiquan Zhou et al.
    Pages 161-169
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Other volumes

  1. Machine Learning in Medical Imaging

Keywords

About this book

This book constitutes the proceedings of the 9th International Workshop on Machine Learning in Medical Imaging, MLMI 2018, held in conjunction with MICCAI 2018 in Granada, Spain, in September 2018.

The 45 papers presented in this volume were carefully reviewed and selected from 82 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging.

Editors and Affiliations

  • Nanjing University, Nanjing, China

    Yinghuan Shi

  • 617A, Science Library, Korea University, Seoul, Korea (Republic of)

    Heung-Il Suk

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

    Mingxia Liu

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