兆宏 潘
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- China
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences
- Institute of Biomedical and Health Engineering
Statistics
- Member for 1 year, 11 months
- 81 challenge submissions
- 55 algorithms run
Activity Overview
ToothFairy2: Multi-Structure Segmentation in CBCT Volumes
Challenge UserThis is the second edition of the ToothFairy challenge organized by the University of Modena and Reggio Emilia with the collaboration of Radboud University Medical Center. The challenge is hosted by grand-challenge and is part of MICCAI2024.
HEad and neCK TumOR Lesion Segmentation, Diagnosis and Prognosis
Challenge UserHECKTOR 2025 is the next iteration of a medical imaging challenge focused on improving automated analysis of head and neck cancer using multimodal PET/CT data. The challenge features three complementary tasks that span the clinical workflow: automatic detection and segmentation of primary tumors and lymph nodes, prediction of recurrence-free survival using imaging and clinical data, and diagnosis of HPV status, which is crucial for treatment decisions. The 2025 edition significantly expands on previous challenges with a larger dataset exceeding, refined evaluation metrics that better assess both detection and segmentation capabilities, and the addition of radiotherapy planning dose maps as an information channel. This challenge aims to advance the development of clinical tools that can aid in treatment planning, outcome prediction, and diagnosis in head and neck cancer patients, ultimately supporting more personalized patient management approaches.
ToothFairy3: Multi-Class Segmentation in CBCT Volumes
Challenge UserToothFairy3, part of the ODIN2025 challenge cluster at MICCAI2025, advances CBCT segmentation with an expanded 77-class dataset and a new emphasis on computational efficiency. It introduces two tasks: a runtime-aware multi-structure segmentation and a novel interactive track for Inferior Alveolar Canal (IAC) segmentation using minimal user input. The challenge supports the development of both automated and prompt-based interactive AI tools to enhance clinical workflows in dentistry and maxillofacial surgery.