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Automatic Model-based 3-D Reconstruction of the Teeth from five Photographs with Predefined Viewing Directions

 
: Wirtz, Andreas; Jung, Florian; Noll, Matthias; Wang, Anqi; Wesarg, Stefan

:

Išgum, Ivana (Ed.) ; Society of Photo-Optical Instrumentation Engineers -SPIE-, Bellingham/Wash.:
Medical Imaging 2021. Image Processing : 15-19 February 2021, Online Only, United States
Bellingham, WA: SPIE, 2021 (Proceedings of SPIE 11596)
ISBN: 978-1-5106-4021-4
ISBN: 978-1-5106-4022-1
Paper 115960S, 16 S.
Conference "Medical Imaging - Image Processing" <2021, Online>
Englisch
Konferenzbeitrag
Fraunhofer IGD ()
Lead Topic: Individual Health; Research Line: Computer vision (CV); Research Line: Machine Learning (ML); Research Line: Modeling (MOD); statistical shape models (SSM); dental imaging; 3D Model Reconstruction; convolutional neural network (CNN); model based segmentations

Abstract
Misalignment of teeth or jaws can impact the ability to chew or speak, increase the risk of gum disease or tooth decay, and potentially influence a person’s (psychological) well-being. Orthodontic treatments of misaligned teeth are complex procedures that employ dental braces to apply forces in order to move the teeth or jaws to their correct position. Photographs are typically used to document the treatment. An automatic analysis of those photographs could support the decision making and monitoring process. In this paper, we propose an automatic model-based end-to-end 3-D reconstruction approach of the teeth from five photographs with predefined viewing directions (i.e. the photographs used in orthodontic treatment documentation). It uses photo- or view-specific 2-D coupled shape models to extract the teeth contours from the images. The shape reconstruction is then carried out by a deformation-based reconstruction approach that utilizes 3-D coupled shape models and minimizes a silhouette-based loss. The optimal model parameters are determined by an optimization which maximizes the overlaps between the projected 2-D outlines of individual teeth of the 3-D model and the contours extracted from the corresponding photograph. After that the point displacements between the projected outline and segmented contour are used to iteratively deform the 3-D shape model of each tooth for all five views. Back-projection into shape space ensures that the 3-D coupled shape model consists of (statistically) valid teeth. Evaluation on 22 data sets shows promising results with an average symmetric surface distance of 0.848mm and an average DICE coefficient of 0.659.

: http://publica.fraunhofer.de/dokumente/N-633921.html