Model-Based human teeth shape recovery from a single optical image with unknown illumination

Authors:
Aly Farag;Shireen Elhabian;Aly Abdelrehim;Wael Aboelmaaty;Allan Farman;David Tasman
Affiliations:
Computer Vision and Image Processing Laboratory, University of Louisville, Louisville, KY;Computer Vision and Image Processing Laboratory, University of Louisville, Louisville, KY;Computer Vision and Image Processing Laboratory, University of Louisville, Louisville, KY;School of Dentistry, University of Louisville, Louisville, KY;School of Dentistry, University of Louisville, Louisville, KY;School of Dentistry, University of Louisville, Louisville, KY
Venue:
MCV'12 Proceedings of the Second international conference on Medical Computer Vision: recognition techniques and applications in medical imaging
Year:
2012

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Abstract

Several existing 3D systems for dental applications rely on obtaining an intermediate solid model of the jaw (cast or teeth imprints) from which the 3D information can be captured. In this paper, we propose a model-based shape-from-shading (SFS) approach which allows for the construction of plausible human jaw models in vivo, without ionizing radiation, using fewer sample points in order to reduce the cost and intrusiveness of acquiring models of patients teeth/jaws over time. The inherent relation between the photometric information and the underlying 3D shape is formulated as a statistical model where the effect of illumination is modeled using Spherical Harmonics (SH) and the partial least square (PLS) approach is deployed to carry out the estimation of dense 3D shapes. Moreover, shape and texture alignment is accomplished using a proposed definition of anatomical jaw landmarks which can be automatically detected. Vis-à-vis dental applications, the results demonstrate a significant increase in accuracy in favor of the proposed approach. In particular, our approach is able to recover geometrical details of tooth occlusal surface as well as mouth floor and ceiling as compared to SFS-based approaches.