Trajectory Grouping with Curvature Regularization for Tubular Structure Tracking

International audience ; Tubular structure tracking is an important task in the fields of computer vision and medical image analysis. The minimal paths-based approaches have exhibited their powerful ability in tracing tubular structures, by which a tubular structure can be naturally treated as a minimal geodesic path computed with a suitable geodesic metric. However, existing minimal paths-based tracing approaches still suffer from difficulty, for instances the shortcuts and short branches combination problems, especially when dealing with the images involving complicated tubular tree structures or background. In this paper, we introduce a new minimal paths-based model for minimally interactive tubular structure centerline extraction in conjunction with a perceptual grouping scheme. Basically, we take into account the prescribed tubular trajectories and curvature-penalized geodesic paths to seek favourable shortest paths. The proposed approach can benefit from the local smoothness prior on tubular structures and the global optimality of the used graph-based path searching scheme. Experimental results on both synthetic and real images prove that the proposed model indeed obtains outperformance comparing with the state-of-the-art minimal path-based tubular structure tracing algorithms.