Image Processing, Computer Vision, Pattern Recognition, and Graphics Lect. Notes Computer Challenges
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Head and Neck Tumor Segmentation

First Challenge, HECKTOR 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings

Editors: Andrearczyk, Vincent, Oreiller, Valentin, Depeursinge, Adrien (Eds.)

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eBook $44.99
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  • ISBN 978-3-030-67194-5
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Softcover $59.99
price for Brazil
  • ISBN 978-3-030-67193-8
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  • Institutional customers should get in touch with their account manager
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About this book

This book constitutes the First 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2020, which was held in conjunction with the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The challenge took place virtually due to the COVID-19 pandemic.

The 2 full and 8 short papers presented together with an overview paper in this volume were carefully reviewed and selected form numerous submissions. This challenge aims to evaluate and compare the current state-of-the-art methods for automatic head and neck tumor segmentation. In the context of this challenge, a dataset of 204 delineated PET/CT images was made available for training as well as 53 PET/CT images for testing. Various deep learning methods were developed by the participants with excellent results.

Table of contents (11 chapters)

Table of contents (11 chapters)
  • Overview of the HECKTOR Challenge at MICCAI 2020: Automatic Head and Neck Tumor Segmentation in PET/CT

    Pages 1-21

    Andrearczyk, Vincent (et al.)

  • Two-Stage Approach for Segmenting Gross Tumor Volume in Head and Neck Cancer with CT and PET Imaging

    Pages 22-27

    Zhu, Simeng (et al.)

  • The Head and Neck Tumor Segmentation Using nnU-Net with Spatial and Channel ‘Squeeze & Excitation’ Blocks

    Pages 28-36

    Xie, Juanying (et al.)

  • Squeeze-and-Excitation Normalization for Automated Delineation of Head and Neck Primary Tumors in Combined PET and CT Images

    Pages 37-43

    Iantsen, Andrei (et al.)

  • Automatic Head and Neck Tumor Segmentation in PET/CT with Scale Attention Network

    Pages 44-52

    Yuan, Yading

Buy this book

eBook $44.99
price for Brazil
  • ISBN 978-3-030-67194-5
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $59.99
price for Brazil
  • ISBN 978-3-030-67193-8
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions & severe weather in the US may cause delays
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
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Bibliographic Information

Bibliographic Information
Book Title
Head and Neck Tumor Segmentation
Book Subtitle
First Challenge, HECKTOR 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings
Editors
  • Vincent Andrearczyk
  • Valentin Oreiller
  • Adrien Depeursinge
Series Title
Image Processing, Computer Vision, Pattern Recognition, and Graphics
Series Volume
12603
Copyright
2021
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-67194-5
DOI
10.1007/978-3-030-67194-5
Softcover ISBN
978-3-030-67193-8
Edition Number
1
Number of Pages
X, 109
Number of Illustrations
3 b/w illustrations, 29 illustrations in colour
Topics