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Accurately segmenting teeth and identifying the corresponding anatomical landmarks on dental mesh models are essential in computer-aided orthodontic treatment. ... Our TS-MDL first adopts an end-to-end iMeshSegNet method (i.e., a variant of the existing MeshSegNet with both improved accuracy and efficiency) to label each tooth on the downsampled scan. ... ACKNOWLEDGMENT This work is supported, in part, by the Ohio State University College of Dentistry, NIHNIDCR DE022816, and NSF#1938533. ...arXiv:2109.11941v3 fatcat:thhndfz4abbp5nb6oz5gifanua
The proposed network takes as input a 3D tooth model and predicts various types of the tooth landmarks and axes. ... This design choice and a set of added components make the proposed network more suitable for extracting sparse landmarks from a given 3D tooth model. ... Specifically, as shown in Fig. 2 , given the paired CBCT image and dental model scanned from a patient in clinics, we first adopt ToothNet  and TSegNet  to faithfully segment tooth and tooth ...arXiv:2111.04212v2 fatcat:rz7xcmcsdrg6vmwyvn627k7wfa