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Head and Neck Tumor Segmentation and Outcome Prediction edited by Vincent Andrearczyk, Valentin Oreiller, Mathieu Hatt, Adrien Depeursinge. [electronic resource] :

Contributor(s): Material type: TextTextPublication details: Cham Springer Nature Switzerland 2023Edition: 1st ed. 2023Description: XI, 257 p. 75 illus., 67 illus. in color. online resourceISBN:
  • 9783031274206
Subject(s): DDC classification:
  • 6
Online resources: Summary: This book constitutes the Third 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2022, which was held in conjunction with the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, on September 22, 2022. 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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Item type Home library Call number Status Notes Date due Barcode Item holds
e-Book e-Book S. R. Ranganathan Learning Hub Online Available Platform:Springer EB2138
Total holds: 0

This book constitutes the Third 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2022, which was held in conjunction with the 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022, on September 22, 2022. 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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