Image Processing, Computer Vision, Pattern Recognition, and Graphics

Deep Learning and Data Labeling for Medical Applications

First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings

Editors: Carneiro, G., Mateus, D., Loïc, P., Bradley, A., Tavares, J.M.R.S., Belagiannis, V., Papa, J.P., Nascimento, J.C., Loog, M., Lu, Z., Cardoso, J.S., Cornebise, J. (Eds.)

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eBook $54.99
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  • ISBN 978-3-319-46976-8
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About this book

This book constitutes the refereed proceedings of two workshops held at the 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016, in Athens, Greece, in October 2016: the First Workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2016, and the Second International Workshop on Deep Learning in Medical Image Analysis, DLMIA 2016. The 28 revised regular papers presented in this book were carefully reviewed and selected from a total of 52 submissions. The 7 papers selected for LABELS deal with topics from the following fields: crowd-sourcing methods; active learning; transfer learning; semi-supervised learning; and modeling of label uncertainty.The 21 papers selected for DLMIA span a wide range of topics such as image description; medical imaging-based diagnosis; medical signal-based diagnosis; medical image reconstruction and model selection using deep learning techniques; meta-heuristic techniques for fine-tuning parameter in deep learning-based architectures; and applications based on deep learning techniques.

Table of contents (28 chapters)

  • HEp-2 Cell Classification Using K-Support Spatial Pooling in Deep CNNs

    Han, Xian-Hua (et al.)

    Pages 3-11

  • Robust 3D Organ Localization with Dual Learning Architectures and Fusion

    Lu, Xiaoguang (et al.)

    Pages 12-20

  • Cell Segmentation Proposal Network for Microscopy Image Analysis

    Akram, Saad Ullah (et al.)

    Pages 21-29

  • Vessel Detection in Ultrasound Images Using Deep Convolutional Neural Networks

    Smistad, Erik (et al.)

    Pages 30-38

  • Convolutional Neural Network for Reconstruction of 7T-like Images from 3T MRI Using Appearance and Anatomical Features

    Bahrami, Khosro (et al.)

    Pages 39-47

Buy this book

eBook $54.99
price for USA (gross)
  • ISBN 978-3-319-46976-8
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $72.00
price for USA
  • ISBN 978-3-319-46975-1
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
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Bibliographic Information

Bibliographic Information
Book Title
Deep Learning and Data Labeling for Medical Applications
Book Subtitle
First International Workshop, LABELS 2016, and Second International Workshop, DLMIA 2016, Held in Conjunction with MICCAI 2016, Athens, Greece, October 21, 2016, Proceedings
Editors
  • Gustavo Carneiro
  • Diana Mateus
  • Peter Loïc
  • Andrew Bradley
  • João Manuel R.S. Tavares
  • Vasileios Belagiannis
  • João Paulo Papa
  • Jacinto C. Nascimento
  • Marco Loog
  • Zhi Lu
  • Jaime S. Cardoso
  • Julien Cornebise
Series Title
Image Processing, Computer Vision, Pattern Recognition, and Graphics
Series Volume
10008
Copyright
2016
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-46976-8
DOI
10.1007/978-3-319-46976-8
Softcover ISBN
978-3-319-46975-1
Edition Number
1
Number of Pages
XIII, 280
Number of Illustrations and Tables
115 b/w illustrations
Topics