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Proceedings Paper

Labeling scheme for surface detection in 3-D images
Author(s): Prakash Adiseshan; Tracy L. Faber
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Paper Abstract

This work addresses the problem of finding surfaces in 3-D images. This problem involves segmentation and parameterization. The solution method we propose is designed to answer the following questions: (1) Is a point (x,y,z) in 3-space a surface point? (2) If so, what is the surface normal at that point, and (3) What are the neighboring voxels in the u and v directions on the surface? We use a labeling scheme to define a surface element, at a point, in (u, v) directions. By restricting the neighborhood volume at a point, we have a small set of labels in u and v directions. A cost functional is set up, in terms of surface normal and labels at a point, following the calculus of variations methodology. Estimation of surface normal at a point depends on normals at neighboring points and label connectivity criteria defined. This also facilitates handling of surfaces that are not smoothly varying. The final solution is found by finding the set of normal and labels at every point that minimize the cost functional. Finally, we apply our method to find surfaces in 3-D synthetic and medical image data.

Paper Details

Date Published: 1 March 1992
PDF: 4 pages
Proc. SPIE 1608, Intelligent Robots and Computer Vision X: Neural, Biological, and 3-D Methods, (1 March 1992); doi: 10.1117/12.135084
Show Author Affiliations
Prakash Adiseshan, Univ. of Texas Southwestern Medical Ctr./Dallas (United States)
Tracy L. Faber, Digital Design (United States)

Published in SPIE Proceedings Vol. 1608:
Intelligent Robots and Computer Vision X: Neural, Biological, and 3-D Methods
David P. Casasent, Editor(s)

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