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为实现以视频速度实时测量，建立一条与血管轴向垂直且在血管径向覆盖血管边缘的测量线作为采样窗口。通过对该测量线光密度分布的分析得到一个可逐帧自适应光密度变化的动态阈值，根据血管边缘区域内光密度曲线的形态特征和管径动态变化的可能范围来判定微血管边缘。建立多项判定规则提高边缘测定的精度并跳过非边缘区以加快处理速度。为进一步提高这种边缘测定的可靠性，在原图像上叠加一个与被测血管边缘位置相一致的动态图形指示。实用结果发现：即使在微血管图像背景复杂和反差较弱的情况下，这种采用自适应阈值和多项判别规则的微血管边缘动态检测方法仍能完成对微血管自律运动的自动跟踪测量
To achieve real-time measurement at video speed, a measurement window perpendicular to the axial direction of the blood vessel and covering the edge of the blood vessel in the radial direction of the blood vessel is set as the sampling window. By analyzing the optical density distribution of the measurement line, a dynamic threshold which can adjust the optical density on a frame-by-frame basis is obtained. The edge of the microvascular is judged according to the morphological characteristics of the optical density curve in the edge region of the blood vessel and the possible range of the dynamic change of the diameter. Establish a number of decision rules to improve the accuracy of edge detection and skip the non-edge area to speed up the processing speed. In order to further improve the reliability of this edge detection, a dynamic pattern indication consistent with the position of the edge of the blood vessel under test is superimposed on the original image. The practical results show that this micro-vascular edge dynamic detection method using adaptive thresholds and multiple discriminant rules can still perform automatic tracking measurement of the autonomic movement of microvessels, even in the case of complex background and weak contrast of microvascular images