利用图谱匹配分割标注VHP数据集

利用TT脑图谱中丰富的结构信息，本文提出了一种自动分割脑图像的方法，并将其用于Visible Human数据集（VHD）的脑图像的分割，这种方法可分为两步，首先，将VHD中的脑图像和TT Atlas配准，通过图像和医学图谱的匹配，可以把图谱中存储的拓朴信息直接映射到ＶＨＤ，然后，利用这个预分割的模板对VHD脑图像进行模糊聚类分割，为自动将模板中的结构信息用于分割，本文利用Chamfer距离变换，提出了一中引入形状因子的FCM聚类算法。

SEGMENTATION AND LABELING OF VISIBLE HUMAN DATASET BASED ON ATLAS

We proposed an automatic segmentation and classification method of multimodal human brain image based on a computerized brain atlas TT Atlas. It could be divided into two steps. Firstly, the object brain data set was registered with the TT atlas by a 3D image matching method. With the help of anatomy structure information of the computerized atlas, we can segment and classify the brain data coarsely. Secondly, the segmentation result was taken as the input of a fuzzy clustering segmentation. In order to use the anatomic structure information directly, a new fuzzy cluster method with a shape factor was introduced, The method is mostly automatically except selection of some intrinsic point pairs for global linear matching method in the first step. At last, this method was used for classification of brain image from VHD.