Medical Image Segmentation Based on Novel Local Order Energy

Image segmentation plays an important role in many medical imaging systems, yet in complex circumstances it is still a challenging problem. Among many difficulties, problem caused by the image intensity inhomogeneity is the key aspect. In this work, we develop a novel localhomogeneous region-based level set segmentation method to tackle this problem. First, we propose a novel local order energy, which interprets the local intensity constraint. And then, we integrate this energy into the objective energy function. After that, we minimize the energy function via a level set evolution process. Extensive experiments are performed to evaluate the proposed approach, showing significant improvements in both accuracy and efficiency, as compared to the state-of-the-art.

• Type: Journal
• Year: 2010
• Where: ACCV
• Authors: LingFeng Wang, Zeyun Yu, Chunhong Pan
• Keywords: ACCV 2010, Computer Vision, Energy Function, Image Intensity Inhomogeneity, Objective Energy Function