Processing and Segmentation of Human Teeth from 2D Images using Weakly Supervised Learning

arXiv:2311.07398v2 Announce Type: replace
Abstract: Teeth segmentation is an essential task in dental image analysis for accurate diagnosis and treatment planning. While supervised deep learning methods can be utilized for teeth segmentation, they often require extensive manual annotation of segmentation masks, which is time-consuming and costly. In this research, we propose a weakly supervised approach for teeth segmentation that reduces the need for manual annotation. Our method utilizes the output heatmaps and intermediate feature maps from a keypoint detection network …

abstract analysis annotation arxiv cs.cv deep learning dental diagnosis human image images masks planning processing segmentation supervised learning treatment type