30 April 2015 Joint detection of anatomical points on surface meshes and color images for visual registration of 3D dental models
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Proceedings Volume 9534, Twelfth International Conference on Quality Control by Artificial Vision 2015; 95340B (2015) https://doi.org/10.1117/12.2182821
Event: The International Conference on Quality Control by Artificial Vision 2015, 2015, Le Creusot, France
Abstract
Computer aided planning for orthodontic treatment requires knowing occlusion of separately scanned dental casts. A visual guided registration is conducted starting by extracting corresponding features in both photographs and 3D scans. To achieve this, dental neck and occlusion surface are firstly extracted by image segmentation and 3D curvature analysis. Then, an iterative registration process is conducted during which feature positions are refined, guided by previously found anatomic edges. The occlusal edge image detection is improved by an original algorithm which follows Canny’s poorly detected edges using a priori knowledge of tooth shapes. Finally, the influence of feature extraction and position optimization is evaluated in terms of the quality of the induced registration. Best combination of feature detection and optimization leads to a positioning average error of 1.10 mm and 2.03°.
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Raphaël Destrez, Raphaël Destrez, Benjamin Albouy-Kissi, Benjamin Albouy-Kissi, Sylvie Treuillet, Sylvie Treuillet, Yves Lucas, Yves Lucas, } "Joint detection of anatomical points on surface meshes and color images for visual registration of 3D dental models", Proc. SPIE 9534, Twelfth International Conference on Quality Control by Artificial Vision 2015, 95340B (30 April 2015); doi: 10.1117/12.2182821; https://doi.org/10.1117/12.2182821
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