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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 (Lecture Notes in Computer Science)

By: Adrien Depeursinge (Edited by) , Valentin Oreiller (Edited by) , Vincent Andrearczyk (Edited by)

Extended Catalogue

Ksh 10,250.00

Format: Paperback or Softback

ISBN-10: 3030671933

ISBN-13: 9783030671938

Collection / Series: Lecture Notes in Computer Science

Collection Type: Publisher collection

Edition statement: 1st ed. 2021

Publisher: Springer Nature Switzerland AG

Imprint: Springer Nature Switzerland AG

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Jan 13th, 2021

Publication Status: Active

Product extent: 109 Pages

Product Classification / Subject(s): Biology, life sciences
Software Engineering
Computer science
Machine learning
Image processing

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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.
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.

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