分割
水准点(测量)
计算机科学
三维模型
鉴定(生物学)
计算机辅助设计
三维重建
人工智能
牙科
计算机视觉
口腔正畸科
医学
工程制图
地图学
工程类
生物
植物
地理
作者
Achraf Ben-Hamadou,Oussama Smaoui,Houda Chaabouni-Chouayakh,A. Rekik,Sergi Pujades,Edmond Boyer,Julien Strippoli,Aurélien Thollot,Hugo Setbon,Cyril Trosset,Edouard Ladroit
出处
期刊:Cornell University - arXiv
日期:2022-01-01
被引量:3
标识
DOI:10.48550/arxiv.2210.06094
摘要
Teeth segmentation and labeling are critical components of Computer-Aided Dentistry (CAD) systems. Indeed, before any orthodontic or prosthetic treatment planning, a CAD system needs to first accurately segment and label each instance of teeth visible in the 3D dental scan, this is to avoid time-consuming manual adjustments by the dentist. Nevertheless, developing such an automated and accurate dental segmentation and labeling tool is very challenging, especially given the lack of publicly available datasets or benchmarks. This article introduces the first public benchmark, named Teeth3DS, which has been created in the frame of the 3DTeethSeg 2022 MICCAI challenge to boost the research field and inspire the 3D vision research community to work on intra-oral 3D scans analysis such as teeth identification, segmentation, labeling, 3D modeling and 3D reconstruction. Teeth3DS is made of 1800 intra-oral scans (23999 annotated teeth) collected from 900 patients covering the upper and lower jaws separately, acquired and validated by orthodontists/dental surgeons with more than 5 years of professional experience.
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