Segmentation of images for gingival growth measurement

Dong-Il Kim; Joseph N. Wilson

doi:10.1117/12.130908

9 December 1992 Segmentation of images for gingival growth measurement

Dong-Il Kim, Joseph N. Wilson

Proceedings Volume 1768, Mathematical Methods in Medical Imaging; (1992) https://doi.org/10.1117/12.130908
Event: San Diego '92, 1992, San Diego, CA, United States

Abstract

The ability to measure gingival volume growth from dental casts would provide a valuable resource for periodontists. This problem is attractive from a computer vision standpoint due to the complexities of data acquisition, segmentation of gingival and tooth surfaces and boundaries, and extraction of features (such as tooth axes) to help solve the correspondence problem for multiple casts. In this paper, a structured light 3-D range finder is used to collect raw data. The most complicated subtask is that of detecting discontinuities such as the gingival margin. Discontinuity detection is hindered both by cast anomalies (such as bubbles and holes generated during the process of dental impression) and by the subtle nature of the discontinuities themselves. First, we discuss an approach to segmenting a dental cast into tooth and gingival units using depth and orientation discontinuities. The visible cast surface is reconstructed by obtaining the minimum of a parameterized functional. The first derivative of the energy functional (which corresponds to the Euler-Lagrange equation) is solved using the multigrid methods. both orientation and depth discontinuities are detected by adding a discrete discontinuity functional to the energy functional. The principal axes and boundaries of the teeth provide the information necessary to determine the region to be measured in estimating gingival growth. Finally, voxels corresponding to growth regions are counted to measure the target volume.

Citation Download Citation

Dong-Il Kim and Joseph N. Wilson "Segmentation of images for gingival growth measurement", Proc. SPIE 1768, Mathematical Methods in Medical Imaging, (9 December 1992); https://doi.org/10.1117/12.130908

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