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Machine Learning in Medical Imaging

10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings

  • Conference proceedings
  • © 2019

Overview

Editors:
  1. Heung-Il Suk

    1. Korea University, Seoul, Korea (Republic of)

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  2. Mingxia Liu

    1. University of North Carolina, Chapel Hill, USA

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  3. Pingkun Yan

    1. Rensselaer Polytechnic Institute, Troy, USA

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  4. Chunfeng Lian

    1. University of North Carolina, Chapel Hill, USA

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11861)

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 2019.

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Table of contents (78 papers)

  1. Front Matter

    Pages i-xviii
    Download chapter PDF

  2. Brain MR Image Segmentation in Small Dataset with Adversarial Defense and Task Reorganization

    • Xuhua Ren, Lichi Zhang, Dongming Wei, Dinggang Shen, Qian Wang
    Pages 1-8

  3. Spatial Regularized Classification Network for Spinal Dislocation Diagnosis

    • Bolin Lai, Shiqi Peng, Guangyu Yao, Ya Zhang, Xiaoyun Zhang, Yanfeng Wang et al.
    Pages 9-17

  4. Globally-Aware Multiple Instance Classifier for Breast Cancer Screening

    • Yiqiu Shen, Nan Wu, Jason Phang, Jungkyu Park, Gene Kim, Linda Moy et al.
    Pages 18-26

  5. Advancing Pancreas Segmentation in Multi-protocol MRI Volumes Using Hausdorff-Sine Loss Function

    • Hykoush Asaturyan, E. Louise Thomas, Julie Fitzpatrick, Jimmy D. Bell, Barbara Villarini
    Pages 27-35

  6. WSI-Net: Branch-Based and Hierarchy-Aware Network for Segmentation and Classification of Breast Histopathological Whole-Slide Images

    • Haomiao Ni, Hong Liu, Kuansong Wang, Xiangdong Wang, Xunjian Zhou, Yueliang Qian
    Pages 36-44

  7. Lesion Detection with Deep Aggregated 3D Contextual Feature and Auxiliary Information

    • Han Zhang, Albert C. S. Chung
    Pages 45-53

  8. MSAFusionNet: Multiple Subspace Attention Based Deep Multi-modal Fusion Network

    • Sen Zhang, Changzheng Zhang, Lanjun Wang, Cixing Li, Dandan Tu, Rui Luo et al.
    Pages 54-62

  9. DCCL: A Benchmark for Cervical Cytology Analysis

    • Changzheng Zhang, Dong Liu, Lanjun Wang, Yaoxin Li, Xiaoshi Chen, Rui Luo et al.
    Pages 63-72

  10. Smartphone-Supported Malaria Diagnosis Based on Deep Learning

    • Feng Yang, Hang Yu, Kamolrat Silamut, Richard J. Maude, Stefan Jaeger, Sameer Antani
    Pages 73-80

  11. Children’s Neuroblastoma Segmentation Using Morphological Features

    • Shengyang Li, Xiaoyun Zhang, Xiaoxia Wang, Yumin Zhong, Xiaofen Yao, Ya Zhang et al.
    Pages 81-88

  12. GFD Faster R-CNN: Gabor Fractal DenseNet Faster R-CNN for Automatic Detection of Esophageal Abnormalities in Endoscopic Images

    • Noha Ghatwary, Massoud Zolgharni, Xujiong Ye
    Pages 89-97

  13. Deep Active Lesion Segmentation

    • Ali Hatamizadeh, Assaf Hoogi, Debleena Sengupta, Wuyue Lu, Brian Wilcox, Daniel Rubin et al.
    Pages 98-105

  14. Infant Brain Deformable Registration Using Global and Local Label-Driven Deep Regression Learning

    • Shunbo Hu, Lintao Zhang, Guoqiang Li, Mingtao Liu, Deqian Fu, Wenyin Zhang
    Pages 106-114

  15. A Relation Hashing Network Embedded with Prior Features for Skin Lesion Classification

    • Wenbo Zheng, Chao Gou, Lan Yan
    Pages 115-123

  16. End-to-End Adversarial Shape Learning for Abdomen Organ Deep Segmentation

    • Jinzheng Cai, Yingda Xia, Dong Yang, Daguang Xu, Lin Yang, Holger Roth
    Pages 124-132

  17. Privacy-Preserving Federated Brain Tumour Segmentation

    • Wenqi Li, Fausto Milletarì, Daguang Xu, Nicola Rieke, Jonny Hancox, Wentao Zhu et al.
    Pages 133-141

  18. Residual Attention Generative Adversarial Networks for Nuclei Detection on Routine Colon Cancer Histology Images

    • Junwei Li, Wei Shao, Zhongnian Li, Weida Li, Daoqiang Zhang
    Pages 142-150

  19. Semi-supervised Multi-task Learning with Chest X-Ray Images

    • Abdullah-Al-Zubaer Imran, Demetri Terzopoulos
    Pages 151-159

  20. Novel Bi-directional Images Synthesis Based on WGAN-GP with GMM-Based Noise Generation

    • Wei Huang, Mingyuan Luo, Xi Liu, Peng Zhang, Huijun Ding, Dong Ni
    Pages 160-168
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Other volumes

  1. Machine Learning in Medical Imaging

Keywords

About this book

This book constitutes the proceedings of the 10th International Workshop on Machine Learning in Medical Imaging, MLMI 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. 

The 78 papers presented in this volume were carefully reviewed and selected from 158 submissions. 
They focus on major trends and challenges in the area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc. 

Editors and Affiliations

  • Korea University, Seoul, Korea (Republic of)

    Heung-Il Suk

  • University of North Carolina, Chapel Hill, USA

    Mingxia Liu, Chunfeng Lian

  • Rensselaer Polytechnic Institute, Troy, USA

    Pingkun Yan

Bibliographic Information

  • Book Title: Machine Learning in Medical Imaging

  • Book Subtitle: 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings

  • Editors: Heung-Il Suk, Mingxia Liu, Pingkun Yan, Chunfeng Lian

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-030-32692-0

  • Publisher: Springer Cham

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

  • Copyright Information: Springer Nature Switzerland AG 2019

  • Softcover ISBN: 978-3-030-32691-3Published: 10 October 2019

  • eBook ISBN: 978-3-030-32692-0Published: 09 October 2019

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XVIII, 695

  • Number of Illustrations: 65 b/w illustrations, 245 illustrations in colour

  • Topics: Image Processing and Computer Vision, Artificial Intelligence

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