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2024, Volume 25, Issue 9

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Frontiers of Information Technology & Electronic Engineering >> 2024, Volume 25, Issue 9 doi: 10.1631/FITEE.2300596

Accurate estimation of 6-DoF tooth pose in 3D intraoral scans for dental applications using deep learning

Affiliation(s): Stomatology Hospital, School of Stomatology, Zhejiang University School of Medicine, Zhejiang Provincial Clinical Research Center for Oral Diseases, Key Laboratory of Oral Biomedical Research of Zhejiang Province, Cancer Center of Zhejiang University, Engineering Research Center of Oral Biomaterials and Devices of Zhejiang Province, Hangzhou 310000, China; Zhejiang University–University of Illinois at Urbana-Champaign Institute, Zhejiang University, Haining 314400, China; Angel Align Inc., Shanghai, Shanghai 200433, China; Hangzhou Dental Hospital, Hangzhou 310006, China; less

Received: 2023-09-01 Accepted: 2024-06-29 Available online: 2024-06-29
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Abstract

A critical step in is to accurately and automatically characterize the orientation and position of individual teeth, which can subsequently be used for treatment planning and simulation in orthodontic tooth alignment. This problem remains challenging because the geometric features of different teeth are complicated and vary significantly, while a reliable large-scale dataset is yet to be constructed. In this paper we propose a novel method for automatic tooth orientation estimation by formulating it as a six-degree-of-freedom (6-DoF) estimation task. Regarding each tooth as a three-dimensional (3D) point cloud, we design a deep with a feature extractor backbone and a two-branch estimation head for estimation. Our model, trained with a novel loss function on the newly collected large-scale dataset (10 393 patients with 280 611 intraoral tooth scans), achieves an average Euler angle error of only 4.780°–5.979° and a translation L1 error of 0.663 mm on a hold-out set of 2598 patients (77 870 teeth). Comprehensive experiments show that 98.29% of the estimations produce a mean angle error of less than 15°, which is acceptable for many clinical and industrial applications.

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