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Head and Neck Tumor Segmentation Outcome Prediction: Second Challenge, HECKTOR 2021, Held Conjunction with MICCAI Strasbourg, France, September 27, ProceedingsHead and Neck Tumor Segmentation Outcome Prediction: Second Challenge, HECKTOR 2021, Held Conjunction with MICCAI Strasbourg, France, September 27, Proceedings

Head and Neck Tumor Segmentation Outcome Prediction: Second Challenge, HECKTOR 2021, Held Conjunction with MICCAI Strasbourg, France, September 27, Proceedings in Bloomington, MN

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Current price: $84.99
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Head and Neck Tumor Segmentation Outcome Prediction: Second Challenge, HECKTOR 2021, Held Conjunction with MICCAI Strasbourg, France, September 27, Proceedings

Head and Neck Tumor Segmentation Outcome Prediction: Second Challenge, HECKTOR 2021, Held Conjunction with MICCAI Strasbourg, France, September 27, Proceedings in Bloomington, MN

Current price: $84.99
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Size: EBook

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This book constitutes the Second 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2021, which was held in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021. The challenge took place virtually on September 27, 2021, due to the COVID-19 pandemic. The 29 contributions presented, as well as an overview paper, 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 325 delineated PET/CT images was made available for training.
This book constitutes the Second 3D Head and Neck Tumor Segmentation in PET/CT Challenge, HECKTOR 2021, which was held in conjunction with the 24th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2021. The challenge took place virtually on September 27, 2021, due to the COVID-19 pandemic. The 29 contributions presented, as well as an overview paper, 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 325 delineated PET/CT images was made available for training.

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