作 者: (康毓秀); (赵锡英); (李彭博); (徐艳);
机构地区: 兰州工业学院后勤管理处,甘肃兰州730050
出 处: 《兰州工业学院学报》 2017年第4期66-69,共4页
摘 要: 为了解决医学诊疗中的医学图像分割问题,提出了一种基于改进的医学图像聚类算法,首先,对原始的医学图像通过直方图进行预处理;其次,将聚类技术应用到预处后的医学图像数据;最后,通过图像颜色标注以产生分割的结果.为了验证算法的可行性与有效性,用来自医院的真实医学图像进行了仿真实验与分析,与传统的医学图像分割技术对比,提出的算法具有更好的视觉效果,在临床上有效好的应用价值. Aiming to solve the problem of medical image segmentation,the paper proposes an improved medical image segmentation algorithm based on clustering. Firstly,the preparation of image histogram is completed. Secondly ,the data clustering method is applied to the achieved image,and finally the segmentation results are gen-erated by the color label. To validate the utility and feasibility,the simulation experiments are applied by using the real images from hospitals. Compared to the traditional techniques,the proposed method achieves the better visual results and has a more application value.