Head and Neck Tumor Segmentation First Challenge, HECKTOR 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings /
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 p...
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| Other Authors: | , , |
| Language: | English |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2021.
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| Edition: | 1st ed. 2021. |
| Series: | Image Processing, Computer Vision, Pattern Recognition, and Graphics ;
12603 |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-3-030-67194-5 |
| Summary: | 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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| Physical Description: | X, 109 p. 32 illus., 29 illus. in color. online resource. |
| ISBN: | 9783030671945 |