Medicine Visible Human True Color Image Segmentation

Medical image segmentation is a technology of dividing the image into segments of various characteristics and abstracting the target interested in. The technology is the focus and key point in medical image processing and analysis, and also the bottleneck, which restricts the development and application of medical image processing.Virtual Human Project, which human further recognize themselves by means of computer and launched by USA, is a significant research topic with wide application value in many fields such as medicine, bionics. At present, the research of human visualization has come into the moment of reconstruction and understanding of body and tissue organ, where the successful segmentation of organs in true color image is the core step, which decides whether the project can progress all right, and furthermore, is the most challenging task in VHP.This paper, using the true data of human thorax slice image from Virtual Human true color data set, studied the following methods of medical image segmentation: methods based on region, methods based on boundary, and methods based on hybrid segmentation—combining region and boundary. Experimental results were given for some classical algorithms. Furthermore, this paper analyzed in-depth the existing medical image segmentation evaluation methods and criteria.Based on above primary work, this paper obtained a few creative achievements about medical image segmentation:(1)Presented a new region-growing algorithm based on adaptive threshold selection and color space feature. Theory analysis and experiment results show that, comparing with traditional region growing algorithm, the new method can improve remarkably the segmentation results from subjective visual effect.(2)Summarized systemically the current hybrid segmentation methods combining region and boundary, from the aspects of theory, algorithm and implementation.(3)Presented an improved hybrid segmentation algorithm based on fuzzy connectivity and Voronoi diagram. Extended the hybrid segmentation method from the old one that can only be used for gray image to the new one that can be used for color image. The experimental results show that this improved method is promising.