3D Thinning is an often required image processing task in order to perform shape analysis in various applications. For researchers in these domains, a fast, flexible and easy to access implementation is required. Open source solutions, as the Insights Segmentation and Registration Toolkit (ITK), are often used for image processing and visualization tasks, due to their wide range of provided algorithms. Unfortunately, ITK’s thinning implementation is computational expensive and allows solely one specific thinning approach. Therefore, this work presents OpenThinning, an open source thinning solution for 3D image data. The implemented algorithm evaluates a moving local neighborhood to find deletable voxels, according to different sets of criteria. In order to reduce the computational effort, all possible local neighborhood setting outputs are stored in a lookup table. To show the effectiveness of OpenThinning, the implementation is compared to the performance of the ITK library.
& Hagen, H.
(2016). OpenThinning: Fast 3D Thinning based on Local Neighborhood Lookups. .