Image Processing, Computer Vision, Pattern Recognition, and Graphics

Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention

International Workshops, LABELS 2019, HAL-MICCAI 2019, and CuRIOUS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings

Editors: Zhou, L., Heller, N., Shi, Y., Xiao, Y., Sznitman, R., Cheplygina, V., Mateus, D., Trucco, E., Hu, X.S., Chen, D., Chabanas, M., Rivaz, H., Reinertsen, I. (Eds.)

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  • ISBN 978-3-030-33642-4
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About this book

This book constitutes the refereed joint proceedings of the 4th International Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2019, the First International Workshop on Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention, HAL-MICCAI 2019, and the Second International Workshop on Correction of Brainshift with Intra-Operative Ultrasound, CuRIOUS 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 8 papers presented at LABELS 2019, the 5 papers presented at HAL-MICCAI 2019, and the 3 papers presented at CuRIOUS 2019 were carefully reviewed and selected from numerous submissions. The LABELS papers present a variety of approaches for dealing with a limited number of labels, from semi-supervised learning to crowdsourcing. The HAL-MICCAI papers cover a wide set of hardware applications in medical problems, including medical image segmentation, electron tomography, pneumonia detection, etc. The CuRIOUS papers provide a snapshot of the current progress in the field through extended discussions and provide researchers an opportunity to characterize their image registration methods on newly released standardized datasets of iUS-guided brain tumor resection.


Table of contents (16 chapters)

Table of contents (16 chapters)
  • Comparison of Active Learning Strategies Applied to Lung Nodule Segmentation in CT Scans

    Pages 3-12

    Zotova, Daria (et al.)

  • Robust Registration of Statistical Shape Models for Unsupervised Pathology Annotation

    Pages 13-21

    Rahbani, Dana (et al.)

  • XiangyaDerm: A Clinical Image Dataset of Asian Race for Skin Disease Aided Diagnosis

    Pages 22-31

    Xie, Bin (et al.)

  • Data Augmentation Based on Substituting Regional MRIs Volume Scores

    Pages 32-41

    Leng, Tuo (et al.)

  • Weakly Supervised Segmentation from Extreme Points

    Pages 42-50

    Roth, Holger (et al.)

Buy this book

eBook $44.99
price for USA in USD (gross)
  • ISBN 978-3-030-33642-4
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $59.99
price for USA in USD
  • ISBN 978-3-030-33641-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Large-Scale Annotation of Biomedical Data and Expert Label Synthesis and Hardware Aware Learning for Medical Imaging and Computer Assisted Intervention
Book Subtitle
International Workshops, LABELS 2019, HAL-MICCAI 2019, and CuRIOUS 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings
Editors
  • Luping Zhou
  • Nicholas Heller
  • Yiyu Shi
  • Yiming Xiao
  • Raphael Sznitman
  • Veronika Cheplygina
  • Diana Mateus
  • Emanuele Trucco
  • X. Sharon Hu
  • Danny Chen
  • Matthieu Chabanas
  • Hassan Rivaz
  • Ingerid Reinertsen
Series Title
Image Processing, Computer Vision, Pattern Recognition, and Graphics
Series Volume
11851
Copyright
2019
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-33642-4
DOI
10.1007/978-3-030-33642-4
Softcover ISBN
978-3-030-33641-7
Edition Number
1
Number of Pages
XX, 154
Number of Illustrations
14 b/w illustrations, 48 illustrations in colour
Topics