Grand Challenge: Head and Neck Tumor Segmentation for MR-Guided Applications (HNTS-MRG) 2024

The Head and Neck Tumor Segmentation for MR-Guided Applications (HNTS-MRG) 2024 Grand Challenge is a 2024 MICCAI Grand Challenge.

PI Fuller presented the keynote virtually and in-person on 2024-10-17T0900, describing the relevant issues in biomedical image segmentation, use-case-specific chalenges in head and neck MRI segmentation, and the application space for mpMRI segmentation in adaptive therapy as part of the planned end-Challenge Live Virtual Event.

The Head and Neck Tumor Segmentation for MR-Guided Applications (HNTS-MRG) 2024 Grand Challenge focuses on advancing automated tumor delineation techniques using Magnetic Resonance (MR) imaging for patients with head and neck cancers. This challenge seeks to address the clinical need for accurate and consistent tumor segmentation, which is critical for improving precision in MR-guided radiotherapy. The challenge invites global participation from researchers in the fields of medical imaging, radiotherapy, and machine learning to develop and test state-of-the-art algorithms capable of reliably identifying and segmenting head and neck tumors from MR images.

Participants will have access to a large, curated dataset of multi-institutional MR images of head and neck cancer patients, with expert-annotated tumor regions. The challenge tasks participants to develop segmentation models that not only perform accurately but also generalize across various anatomical structures, imaging protocols, and patient populations. MR-guided radiotherapy demands precise delineation of tumor boundaries to minimize damage to surrounding healthy tissue, making automated segmentation tools a valuable asset in clinical workflows.

The challenge evaluates submitted models based on segmentation accuracy, robustness, and computational efficiency. Metrics such as Dice Similarity Coefficient (DSC), Hausdorff Distance, and execution time will be used to rank the algorithms. Successful models could significantly impact adaptive radiotherapy, enabling real-time treatment adjustments based on updated MR images. The HNTS-MRG 2024 Grand Challenge offers an exciting opportunity for interdisciplinary collaboration, aiming to drive innovation in MR-guided cancer treatment and improve patient outcomes through enhanced imaging and computational techniques.