The first clinically derived Mandibular Defect Dataset, comprising 147 models of various mandibular defects.
Each model is manually annotated by experienced surgeons, and all processing workflows strictly adhere to clinical standards. This dataset accurately represents the complexity of clinical defect boundaries and the diverse anatomical structures of individual patients, making it a valuable resource for developing AI models that exhibit improved generalizability and adaptability in mandibular reconstruction. Additionally, the dataset provides HCL classification diagnoses and relevant information for each defect model, thereby supporting more diverse clinical research in the future.
Funding
Natural Science Foundation of Shanghai (No.24ZR1443700)
Fundamental Research Funds for the Central Universities (No.YG2023LC05)
SJTU Trans-med Awards Research (No.20230104)
CAMS Innovation Fund for Medical Sciences (CIFMS) (No.2019-I2M-5-037)
Project 21DZ2271700-1 from Shanghai Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention