Overview
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 13626)
Included in the following conference series:
Conference proceedings info: HECKTOR 2022.
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About this book
The 22 contributions presented, as well as an overview paper, were carefully reviewed and selected from 24 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 883 delineated PET/CT images was made available for training.
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Keywords
- head and neck cancer
- automatic segmentations
- classification
- computer vision
- computerized tomography
- deep learning
- medical imaging
- health informatics
- image analysis
- image processing
- image segmentation
- machine learning
- medical images
- neural networks
- pattern recognition
- performance, design, evaluation
- segmentation methods
- radiomics
Table of contents (24 papers)
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Head and Neck Tumor Segmentation and Outcome Prediction
Editors and Affiliations
Bibliographic Information
Book Title: Head and Neck Tumor Segmentation and Outcome Prediction
Book Subtitle: Third Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings
Editors: Vincent Andrearczyk, Valentin Oreiller, Mathieu Hatt, Adrien Depeursinge
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-031-27420-6
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023
Softcover ISBN: 978-3-031-27419-0Published: 19 March 2023
eBook ISBN: 978-3-031-27420-6Published: 17 March 2023
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XI, 257
Number of Illustrations: 8 b/w illustrations, 67 illustrations in colour
Topics: Computer Imaging, Vision, Pattern Recognition and Graphics, Signal, Image and Speech Processing, Machine Learning, Bioinformatics