3D-U-SAM Network For Few-shot Tooth Segmentation in CBCT Images

arXiv:2309.11015v2 Announce Type: replace-cross
Abstract: Accurate representation of tooth position is extremely important in treatment. 3D dental image segmentation is a widely used method, however labelled 3D dental datasets are a scarce resource, leading to the problem of small samples that this task faces in many cases. To this end, we address this problem with a pretrained SAM and propose a novel 3D-U-SAM network for 3D dental image segmentation. Specifically, in order to solve the problem of using 2D pre-trained …

abstract arxiv cases cs.lg datasets dental eess.iv few-shot image images network representation sam samples segmentation small treatment type