Combining shape-based and gray-level interpolations

Roberto A. Lutufo; Gabor T. Herman; Jayaram K. Udupa

doi:10.1117/12.131085

22 September 1992 Combining shape-based and gray-level interpolations

Roberto A. Lutufo, Gabor T. Herman, Jayaram K. Udupa

Proceedings Volume 1808, Visualization in Biomedical Computing '92; (1992) https://doi.org/10.1117/12.131085
Event: Visualization in Biomedical Computing, 1992, Chapel Hill, NC, United States

Abstract

Sectional images generated by medical scanners usually have lower interslice resolution than resolution within the slices. Shape-based interpolation is a method of interpolation that can be applied to the segmented 3-D volume to create an isotropic data set. It uses a distance transform applied to every slice prior to estimation of intermediate binary slices. Gray-level interpolation has been the classical way of estimating intermediate slices. The method reported here is a combination of these two forms of interpolation, using the local gradient as a normalizing factor of the combination. Overall, this combination of the methods performs better than either of them applied individually.

Citation Download Citation

Roberto A. Lutufo, Gabor T. Herman, and Jayaram K. Udupa "Combining shape-based and gray-level interpolations", Proc. SPIE 1808, Visualization in Biomedical Computing '92, (22 September 1992); https://doi.org/10.1117/12.131085

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