Region Segmentation Based on Texture Analysis in MRI Data
基于纹理分析的磁共振图象区域分割

In this paper, a texture analysis method for medical MRI region segmentation is presented, aimed at discrimination of macro anatomical structure in the cerebral image data. Four second-order statistical texture parameters, computed by using an isotropic gray-value concurrence, and the local fractal dimension compose a feature space, then a two-step classification procedure is applied to this space: a K-Means method is firstly used for obtaining binary-decision and follows a probabilistic relaxation for computing the membership probability of each voxel.