Combining shape-based and gray-level interpolations

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.