Model-based medical image segmentation: a level set approach
Pan Lin, Chong-Xun Zheng, Yong Yang · 2004
Level set method has been widely applied to medical image segmentation and analysis. This method requires the definition of a speed function that governs model deformation. In this paper, a new speed function for level set framework is proposed. The region intensity information, instead of the image gradient information, is incorporated into the level set framework. This new speed function is particular well adapted to segmentation of region of interesting. We illustrate the performance of the new algorithm on MR images. The experimental results show that incorporating region intensity information into the level set framework, an accurate and robust segmentation can be achieved.