An Improved Medical Image Segmentation Algorithm Based On Clustering Techniques

aimed to solve the problem of the medical image segmentation and apply to medical treatment or diagnose in practice, the paper proposed an improved medical image segmentation algorithm based on improved clustering analysis. Firstly, in order to increase the quality of original medical segmental image, the preparation procedure based on histogram equalization is performed; secondly, for the generation of accurate segmental region, the improved clustering analysis techniques based on data analysis is introduced and applied to process medical image data. Finally, the image labels are determined according to achieved clustering results. Compared to the traditional medical image segmentation, the proposed algorithm has better results of vision effect, and can be extensively used in medical treatment or medical image diagnose. Experiments on real medical images generated from local hospital illustrated that proposed algorithm can achieve better performance outperformed the traditional methods.