Studying Of Edge Detection Of Medical CT Image On Wavelet Transform

Many fields related to image analysis are based on the edge detection of digital images, such as image segmentation, recognition of target region, shape extraction from regional areas and so on. The edge detection of digital image is an important attribute for extracting image characteristics in image recognition. It is also the first step in image understanding and image analysis. It has become one of the most active issues in the field related to machine vision research. Comparing with ordinary images, medical CT images are often fuzzy and with heterogeneity. First, they have ambiguities in gray-scale, signal values coming from one tissue will have drastic changes. Secondly, because of the partial effect, some places on the border of the tissue often contain two substances.In this paper, we set focus on the methods of detecting medical CT image edges based on wavelet transform. We firstly summarize the basic theory on edge detection of images, and introduce some new domestic and foreign research directions on this field; Then, we introduce the theory on wavelet transform and the theory of edge detection of image based on wavelet transform; At last, we mainly study multi-scale methods of detecting image edges based on wavelet transform, citing several improved methods, comparing the results of these methods. Then we propose an improved adaptive method based on two improved methods, the main objective of this improved algorithm is to enhance the quality of detecting medical CT image edges with minimal affection of fuzzy signals and all of the characteristics of the edge, and we verify the improved algorithm's performance by doing experiments.