A New Clustering Segmentation Algorithm of 3D Medical Data Field Based on Density-isoline

Direct 3D volume segmentation is one of the difficult and hot research fields in 3D medical data field processing. Using the clustering and analyzing techniques of data mining, a new clustering and segmentation algorithm is presented. Firstly, According to the physical means of the medical data, the data field is preprocessed to speed up succeed processing. Secondly, the paper deduces and analyzes the clustering and segmentation algorithm and presents some methods to increase the process speed. Finally, the experimental results show that the algorithm has high accuracy when used to segment complicated medical tissue and can improve process speed greatly.