As the base of tissues' segmentation

measurement and analysis in angiographic images

edge-detection is one of the emphases in research for the angiographic image's characteristics of low signal-to-noise ratio

plentiful low-level textures

and gently ramped edges. Edge-detection is the base of tissues' segmentation

measurement and analysis in angiographic images.In general

digital angiographic image's signal-to-noise ratio is low

and there are plenty of low-level textures. Moreover

almost all of the edges are ramp and weak ones. The edge-detection is still one of the emphases for research and clinical applications. This paper presents a new method for detection of the edges in digital angiographic images. We found that histograms of local regions across edges of images are statistically different from that of those where no edge is crossed. This difference can be utilized for the detection of edges of angiographic images. We propose a maximum statistical relativity (MSR) algorithm that is a kind of matching filter. As a result

the edge-detection algorithm is not sensitive to noise and low-level textures of images.