Semi-automated registration and segmentation for gingival tissue volume measurement on 3D OCT images.

Abstract

The change in gingival tissue volume may be used to indicate changes in gingival inflammation, which may be useful for the clinical assessment of gingival health. Properly quantifying gingival tissue volume requires a robust technique for accurate registration and segmentation of longitudinally captured 3-dimensional (3D) images. In this paper, a semi-automated registration and segmentation method for micrometer resolution measurement of gingival-tissue volume is proposed for 3D optical coherence tomography (OCT) imaging. For quantification, relative changes in gingiva tissue volume are measured based on changes in the gingiva surface height using the tooth surface as a reference. This report conducted repeatability tests on this method drawn from repeated scans in one patient, indicating an error of the point cloud registration method for oral OCT imaging is 63.08 ± 4.52µm (1σ), and the measurement error of the gingival tissue average thickness is -3.40 ± 21.85µm (1σ).