The Practical Application of Watershed Algorithm in CT Image
XU Hong-y · Zhongguo yixue wulixue zazhi · 2014
Objective: The watershed algorithm has been widely used in the field of image segmentation, because the capability of restraining noise is weak and the over segmentation phenomenon of most images which make it is difficult to use watershed image segmentation only. According to the over segmentation of watershed algorithm, we propose an improved watershed algorithm, which can effectively restrain the over segmentation phenomenon. Methods: First, Gauss filter processing the input image, and then uses the Sobel operator of image for gradient magnitude, then calculating the multiscale image segmentation,Finally, to achieve the purpose of the segmentation of image threshold segmentation and multi scale transform, and converting it to the pseudo color image to optimize the segmentation results, at the same time, the effective treatment of the over segmentation problem can make the image segmentation's results more apparently. Results: The simulation results show that,compared with the traditional watershed segmentation algorithm, alleviate the over segmentation 's problem, which obtained better segmentation results. Conclusions: In this paper, the traditional watershed algorithm is effectively improved, and applied in the segmentation of medical image of CT, so that the different tissue contour of the image is well differentiated. It can reduce the over segmentation points of the image, so that each region of the image is easier to judge.