Accelerated Local Binary Fitting Scheme for Medical Images Segmentation

Geometric and geodesic active contours are typical approaches for medical image segmentation. Specially, local binary fitting (LBF) effectively takes advantage of the local intensity average in the energy functional to overcome segmentation difficulties caused by intensity inhomogeneity and ruptured edges. Despite promising results, the convergence rate of LBF is too slow. In this paper, we proposed a new efficient implementation for LBF based on the additive operator splitting scheme. In more detail, the multi-dimensional deformation equation of LBF is decomposed into some one-dimensional equations which can be efficiently solved by Tomas algorithm. Experimental results demonstrated that the proposed algorithm performs better than LBF in terms of both CPU time and solution quality.

Keywords:

Geometric active contours , level set , local binary fitting , additive operator splitting , image segmentation