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 local-homogeneous 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. © 2011 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Wang, L., Yu, Z., & Pan, C. (2011). Medical image segmentation based on novel local order energy. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6493 LNCS, pp. 148–159). https://doi.org/10.1007/978-3-642-19309-5_12
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