造影图象的边缘检测是造影图象的组织或器官分割、测量和分析的基础.由于造影图象的信噪比低、低电平纹理多,而且大量边缘是渐变的小幅度微弱边缘,因而其检测一直是造影图象研究与临床应用的重点之一.针对这一问题,提出了一种检测数字造影图象边缘的新方法.由于图象边缘区域与非边缘区域的局部直方图明显不同,因而可以利用这种差别来检测图象的边缘,同时还基于局部直方图构造了一种匹配滤波器算法——最大统计相关算法,该方法不敏感于图象的噪声和低电平纹理,而且能够有效地从噪声和纹理中分离提取造影图象的微弱边缘.

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.