{"ID":2838429,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.16936","arxiv_id":"2511.16936","title":"Shape-preserving Tooth Segmentation from CBCT Images Using Deep Learning with Semantic and Shape Awareness","abstract":"Background:Accurate tooth segmentation from cone beam computed tomography (CBCT) images is crucial for digital dentistry but remains challenging in cases of interdental adhesions, which cause severe anatomical shape distortion. Methods: To address this, we propose a deep learning framework that integrates semantic and shape awareness for shape-preserving segmentation. Our method introduces a target-tooth-centroid prompted multi-label learning strategy to model semantic relationships between teeth, reducing shape ambiguity. Additionally, a tooth-shape-aware learning mechanism explicitly enforces morphological constraints to preserve boundary integrity. These components are unified via multi-task learning, jointly optimizing segmentation and shape preservation. Results: Extensive evaluations on internal and external datasets demonstrate that our approach significantly outperforms existing methods. Conclusions: Our approach effectively mitigates shape distortions and providing anatomically faithful tooth boundaries.","short_abstract":"Background:Accurate tooth segmentation from cone beam computed tomography (CBCT) images is crucial for digital dentistry but remains challenging in cases of interdental adhesions, which cause severe anatomical shape distortion. Methods: To address this, we propose a deep learning framework that integrates semantic and...","url_abs":"https://arxiv.org/abs/2511.16936","url_pdf":"https://arxiv.org/pdf/2511.16936v1","authors":"[\"Zongrui Ji\",\"Zhiming Cui\",\"Na Li\",\"Qianhan Zheng\",\"Miaojing Shi\",\"Ke Deng\",\"Jingyang Zhang\",\"Chaoyuan Li\",\"Xuepeng Chen\",\"Yi Dong\",\"Lei Ma\"]","published":"2025-11-21T04:15:07Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false}