Curve-to-Image Based Non-Rigid Registration of Digital Photos and Quantitative Light-Induced Fluorescence Images in Dentistry

Abstract

Decalcification is an undesirable effect that can arise during orthodontic treatment. In digital photographs, it appears as white spot lesions, i.e. white spots on the tooth surface. To asses the extent of demineralization in a tooth, quantitative light-induced fluorescence (QLF) is used. We propose a method to match digital photographs and QLF images of decalcified teeth, based on the idea of curve-to-image matching. It extracts a curve representing the shape of the tooth from the QLF image and aligns it to the photo. The registration problem is formulated as minimization problem where the objective functional consists of a data term and a higher order, linear elastic prior for the deformation. The data term is constructed using the signed distance function of the tooth region shown in the photo, which is determined in a pre-processing step by classifying the photo into tooth and non-tooth regions. The resulting minimization problem is reformulated as a nonlinear least-square problem and solved numerically using Gauss-Newton. The evaluation is based on 150 image pairs captured from 32 patients. The correctness of the matching is confirmed by visual inspection of dental experts and the alignment improvement quantified using mutual information. The curve-to-image matching idea can be extended to surface-to-voxel tasks.