Staircase-Aware Smoothing of Medical Surface Meshes

Abstract

The evaluation of spatial relationships between anatomic structures is a major task in surgical planning. Surface models generated from medical image data (intensity, binary) are often used for visualization and 3D measurement of extents and distances between neighboring structures. In applications for intervention or radiation treatment planning, the surface models should exhibit a natural look (referring to smoothness of the surface), but also be accurate. Smoothing algorithms allow to reduce artifacts from mesh generation, but often degrade accuracy. In particular, relevant features may be removed and distances between adjacent structures get changed. Thus, we present a modification to common mesh smoothing algorithms, which allows to focus the smoothing effect directly to previously identified staircase artifacts. This allows to preserve non-artifact features. The approach has been applied to various data to demonstrate the suitability for different anatomical shapes. The results are compared to the ones of standard uniform mesh smoothing algorithms and are evaluated regarding smoothness and accuracy with respect to the application within surgical planning.