基于脑图谱和模糊聚类的磁共振图像分割标注

利用TT Atlas中丰富的结构信息,文章提出了一种自动分割脑MRI(magnetic resonance image)图像的方法.这种方法可分为两步.首先,将MRI图像和TT Atlas配准,通过图像和医学图谱的匹配,利用图谱中结构信息的先验知识,就可以对图像作初步的分割标注.然后,利用这个预分割的模板对MRI图像进行模糊聚类分割,从而提高分割的精度.为了自动地将预模板中的结构信息用于分割,文章还提出了一种引入形状因子的FCM聚类算法.除了在匹配时需要手工定出一些点之外,该方法基本上是自动的.

Segmentation and Classification of MRI Based on FCM Clustering Algorithm and Computerized Brain Atlas

An automatic segmentation and classification method of magnetic resonance image of human brain based on a computerized brain atlas-TT atlas is introduced in this paper. The algorithm could be divided into two steps. Firstly, the object brain dataset is registered with the TT atlas by a 3D image matching method. With the help of anatomy structure information of the computerized atlas, the brain image is segmented and classified coarsely. Secondly, the segmentation result is taken as the input of a fuzzy cluster segmentation. In order to use the anatomic structure information directly, a new fuzzy cluster method with a shape factor is introduced, the method is mostly and automatically except selection of some intrinsic point pairs for global linear matching method in the first step.