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Head and neck tumor segmentation and outcome prediction : third challenge, HECKTOR 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Head and Neck Tumor Segmentation Challenge (3rd : 2022 : Singapor...最新文献

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Overview of the HECKTOR Challenge at MICCAI 2022: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT. 2022 年 MICCAI 上的 HECKTOR 挑战赛概述:PET/CT 中的头颈部肿瘤自动分割和结果预测。
Vincent Andrearczyk, Valentin Oreiller, Moamen Abobakr, Azadeh Akhavanallaf, Panagiotis Balermpas, Sarah Boughdad, Leo Capriotti, Joel Castelli, Catherine Cheze Le Rest, Pierre Decazes, Ricardo Correia, Dina El-Habashy, Hesham Elhalawani, Clifton D Fuller, Mario Jreige, Yornna Khamis, Agustina La Greca, Abdallah Mohamed, Mohamed Naser, John O Prior, Su Ruan, Stephanie Tanadini-Lang, Olena Tankyevych, Yazdan Salimi, Martin Vallières, Pierre Vera, Dimitris Visvikis, Kareem Wahid, Habib Zaidi, Mathieu Hatt, Adrien Depeursinge

This paper presents an overview of the third edition of the HEad and neCK TumOR segmentation and outcome prediction (HECKTOR) challenge, organized as a satellite event of the 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2022. The challenge comprises two tasks related to the automatic analysis of FDG-PET/CT images for patients with Head and Neck cancer (H&N), focusing on the oropharynx region. Task 1 is the fully automatic segmentation of H&N primary Gross Tumor Volume (GTVp) and metastatic lymph nodes (GTVn) from FDG-PET/CT images. Task 2 is the fully automatic prediction of Recurrence-Free Survival (RFS) from the same FDG-PET/CT and clinical data. The data were collected from nine centers for a total of 883 cases consisting of FDG-PET/CT images and clinical information, split into 524 training and 359 test cases. The best methods obtained an aggregated Dice Similarity Coefficient (DSCagg) of 0.788 in Task 1, and a Concordance index (C-index) of 0.682 in Task 2.

本文概述了第三届头颈部肿瘤分割和结果预测(HECKTOR)挑战赛的情况,该挑战赛是 2022 年第 25 届国际医学影像计算和计算机辅助干预会议(MICCAI)的一项卫星活动。挑战赛包括两项任务,涉及对头颈部癌症(H&N)患者的 FDG-PET/CT 图像进行自动分析,重点是口咽部区域。任务 1 是根据 FDG-PET/CT 图像全自动分割 H&N 原发肿瘤总体积(GTVp)和转移淋巴结(GTVn)。任务 2 是根据相同的 FDG-PET/CT 和临床数据全自动预测无复发生存率(RFS)。数据收集自九个中心,共计 883 个病例,包括 FDG-PET/CT 图像和临床信息,分为 524 个训练病例和 359 个测试病例。最佳方法在任务 1 中获得了 0.788 的综合骰子相似系数(DSCagg),在任务 2 中获得了 0.682 的一致性指数(C-index)。
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Head and neck tumor segmentation and outcome prediction : third challenge, HECKTOR 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings. Head and Neck Tumor Segmentation Challenge (3rd : 2022 : Singapor...
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