A New Tubular Structure Tracking Algorithm Based On Curvature-Penalized Perceptual Grouping

Abstract

In this paper, we propose a new minimal path-based framework for minimally interactive tubular structure tracking in conjunction with a perceptual grouping scheme. The minimal path models have shown great advantages in tubular structures tracing. However, they suffer from shortcuts or short branches combination problems especially in the case of tubular network with complicated structures or background. Thus, we utilize the curvature-penalized minimal paths and the prescribed tubular trajectories to seek the desired shortest path. The proposed approach benefits from the local smoothness prior on tubular structures and the global optimality of the graph-based path searching scheme. Experimental results on synthetic and real images prove that the proposed model indeed obtains outperformance to state-of-the-art minimal path-based algorithms.