Region-based image segmentation with local signed difference energy

Intensity inhomogeneity often causes considerable difficulties in image segmentation. To tackle this problem, we propose a new region-based level set method. The proposed method considers the local image information by describing it as a novel local signed difference (LSD) energy, which possesses both local separability and global consistency. The LSD energy term is integrated into an objective energy functional, which is minimized via a level set evolution process. Extensive experiments are performed to evaluate the proposed method, showing improvements in both accuracy and efficiency, as compared with the state-of-the-art approaches.

► We propose a new local signed difference (LSD) energy in level set segmentation framework. ► LSD energy possesses both local separability and global consistency. ► Segmentation accuracy is improved as compared with the state-of-the-art approaches.