基于超椭球模糊聚类的人脑磁共振图象分割

Human Brain Magnetic Resonance Image Segmentation Based on Hyperellipsoidal Fuzzy Clustering Algorithm

通常使用的聚类分割方法认为样本的分布是超球形的，然而，这并不符合人脑磁共振ＭＲ（ｍａｇｎｅｔ－ｉｃｒｅｓｏｎａｎｃｅ）图象的真正特点．针对这一缺陷，提出了一种基于超椭球模糊聚类的人脑ＭＲ图象分割方法．实验结果表明，这种分割方法能有效地将人脑ＭＲ图象分割为灰质和白质两种组织，并具有较高的效率和分割精度．

The commonly used cluster based segmentation method assumes that the sample distribution is hyperspherical, but this kind of assumption is not consistent with the real characteristic of the human brain MR (magnetic resonance) image. In order to surmount this drawback, a new algorithm for segmenting MR image based on hyperellipsoidal fuzzy clustering is presented in this paper. Provided experimental results indicate that the proposed strategy is feasible for classifying the white matter and the gray matter of the brain, and has the merits of both high efficiency and remarkable accuracy.