In order to participate in this challenge you will have to sign an End User Agreement (EUA) for downloading the data. More information will come.
Once participants submit their results on the test set to the challenge organizers via the challenge website, they will be considered fully vested in the challenge, so that their performance results (without identifying the participant unless permission is granted) will become part of any presentations, publications, or subsequent analyses derived from the Challenge at the discretion of the organizers.
An overview paper will be written by the organizing team’s members. To be eligible for the official ranking and prize, the participating teams must submit a paper reporting their method. The participants can submit their results separately elsewhere when citing the overview paper , and (if so) no embargo will be applied. In addition, the following paper  should also always be referenced.
 Overview of the HECKTOR challenge at MICCAI 2021: Automatic Head and Neck Tumor Segmentation and Outcome Prediction in PET/CT images. Vincent Andrearczyk, Valentin Oreiller, Sarah Boughdad, Joel Castelli, Catherine Chez Le Rest, Hesham Elhalawani,Mario Jreige, John O. Prior, Martin Vallières, Dimitris Visvikis, Mathieu Hatt, Adrien Depeursinge
 Automatic Segmentation of Head and Neck Tumors and Nodal Metastases in PET-CT scans. Vincent Andrearczyk, Valentin Oreiller, Martin Vallières, Joel Castelli, Hesham Elhalawani, Mario Jreige, Sarah Boughdad, John O. Prior, Adrien Depeursinge. In: Medical Imaging with Deep Learning. MIDL 2020.