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Image Processing, Computer Vision, Pattern Recognition, and Graphics

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures

First International Workshop, UNSURE 2019, and 8th International Workshop, CLIP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings

Editors: Greenspan, H., Tanno, R., Erdt, M., Arbel, T., Baumgartner, C., Dalca, A., Sudre, C.H., Wells III, W.M., Drechsler, K., Linguraru, M.G., Oyarzun Laura, C., Shekhar, R., Wesarg, S., González Ballester, M.Á. (Eds.)

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eBook $44.99
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  • ISBN 978-3-030-32689-0
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
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  • Immediate eBook download after purchase
Softcover $59.99
price for USA in USD
  • ISBN 978-3-030-32688-3
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  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
About this book

This book constitutes the refereed proceedings of the First International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2019, and the 8th International Workshop on Clinical Image-Based Procedures, CLIP 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019.

For UNSURE 2019, 8 papers from 15 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world.

CLIP 2019 accepted 11 papers from the 15 submissions received. The workshops provides a forum for work centred on specific clinical applications, including techniques and procedures based on comprehensive clinical image and other data. 

Table of contents (19 chapters)

Table of contents (19 chapters)
  • Probabilistic Surface Reconstruction with Unknown Correspondence

    Pages 3-11

    Madsen, Dennis (et al.)

  • Probabilistic Image Registration via Deep Multi-class Classification: Characterizing Uncertainty

    Pages 12-22

    Sedghi, Alireza (et al.)

  • Propagating Uncertainty Across Cascaded Medical Imaging Tasks for Improved Deep Learning Inference

    Pages 23-32

    Mehta, Raghav (et al.)

  • Reg R-CNN: Lesion Detection and Grading Under Noisy Labels

    Pages 33-41

    Ramien, Gregor N. (et al.)

  • Fast Nonparametric Mutual-Information-based Registration and Uncertainty Estimation

    Pages 42-51

    Agn, Mikael (et al.)

Buy this book

eBook $44.99
price for USA in USD
  • ISBN 978-3-030-32689-0
  • 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 978-3-030-32688-3
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
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Bibliographic Information

Bibliographic Information
Book Title
Uncertainty for Safe Utilization of Machine Learning in Medical Imaging and Clinical Image-Based Procedures
Book Subtitle
First International Workshop, UNSURE 2019, and 8th International Workshop, CLIP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings
Editors
  • Hayit Greenspan
  • Ryutaro Tanno
  • Marius Erdt
  • Tal Arbel
  • Christian Baumgartner
  • Adrian Dalca
  • Carole H. Sudre
  • William M. Wells III
  • Klaus Drechsler
  • Marius George Linguraru
  • Cristina Oyarzun Laura
  • Raj Shekhar
  • Stefan Wesarg
  • Miguel Ángel González Ballester
Series Title
Image Processing, Computer Vision, Pattern Recognition, and Graphics
Series Volume
11840
Copyright
2019
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-32689-0
DOI
10.1007/978-3-030-32689-0
Softcover ISBN
978-3-030-32688-3
Edition Number
1
Number of Pages
XVII, 192
Number of Illustrations
7 b/w illustrations, 76 illustrations in colour
Topics