PMCanalSeg：用于从 3D CBCT 图像自动分割翼腭管和下颌管的数据集

In orthognathic surgery, accurate segmentation of the pterygopalatine and mandibular canals in maxillofacial cone-beam computed tomography (CBCT) scans is crucial. However, deep learning models face challenges due to data scarcity, privacy restrictions, and ethical barriers. To address this challenge and advance the development of pterygopalatine and mandibular canal segmentation techniques in maxillofacial CBCT scans, we carefully constructed and publicly available a large dataset for pterygopalatine and mandibular canal segmentation in maxillofacial CBCT scans. This dataset includes 191 patient cases and comprehensively covers the key anatomical structures of the maxillary pterygopalatine and mandibular canals, both of which are crucial in orthognathic surgery. Notably, this dataset is the first to include data on the maxillary pterygopalatine canal, filling a significant gap in this field. The release of this dataset will greatly accelerate the development of deep learning-based segmentation methods, provide clinicians with more accurate reconstruction tools, and ultimately improve the safety and efficiency of surgical procedures.