HECKTOR 2026 is a challenge held in conjunction with MICCAI 2026 that advances machine learning solutions for head and neck cancer by unifying tumor segmentation, radiological TN staging, and recurrence-free survival prediction into a single end-to-end clinical pipeline. It leverages a large, multi-institutional dataset of multimodal FDG PET, CT, and clinical data to promote the development of robust, generalizable, and clinically translatable AI models.
A strong submission should clearly identify its contribution and evaluate it appropriately.
Docker-based algorithm submission
Participants submit Docker containers that process multimodal imaging and clinical data to perform segmentation, TN staging, and prognosis prediction in a single pipeline, with evaluation across three phases: Sanity Check, Validation, and Testing.
Conference paper
Teams must submit a 6–12 page paper in LNCS format via OpenReview to be eligible for official ranking; the paper must describe the primary approach, results, and methodology used in the challenge.