Thinning is a widely used pre-processing step in digital image processing and pattern recognition. It is an iterative layer by layer erosion until only the "skeletons" of the objects are left. We proposed some parallel thinning algorithms that are based on some sufficient conditions for topology preservation.

Thinning is a frequently used method for skeletonization by modeling the fire-front propagation. We proposed some sequential and parallel 2D thinning algorithms capable of producing topologically correct skeletons.

The thinning is an iterative layer by layer erosion until only the "skeletons" of the objects are left. We proposed various 3D thinning algorithms capable of extracting medial lines or medial surfaces as well.

Skeletonization has been successfully applied in the following three medical applications: assessment of laryngotracheal stenosis, assessment of infrarenal aortic aneurysm, and unravelling the colon.

A method for computationally efficient skeletonization of three-dimensional tubular structures was proposeded. It is specifically targeting skeletonization of vascular and airway tree structures in medical images but it is general and applicable to many other skeletonization tasks.