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Overview of the HECKTOR Challenge at MICCAI 2020: Automatic Head and Neck Tumor Segmentation in PET/CT

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Andrearczyk, V. | Oreiller, V. | Jreige, M. | Vallières, M. | Castelli, J. | Elhalawani, H. | Boughdad, S. | Prior, J.O. | Depeursinge, A.

Edité par CCSD ; Springer Science and Business Media Deutschland GmbH -

International audience. This paper presents an overview of the first HEad and neCK TumOR (HECKTOR) challenge, organized as a satellite event of the 23rd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2020. The task of the challenge is the automatic segmentation of head and neck primary Gross Tumor Volume in FDG-PET/CT images, focusing on the oropharynx region. The data were collected from five centers for a total of 254 images, split into 201 training and 53 testing cases. The interest in the task was shown by the important participation with 64 teams registered and 18 team submissions. The best method obtained a Dice Similarity Coefficient (DSC) of 0.7591, showing a large improvement over our proposed baseline method with a DSC of 0.6610 as well as inter-observer DSC agreement reported in the literature (0.69). © 2021, Springer Nature Switzerland AG.

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