Adaptive detection of microvascular edge in microcirculatory images for auto-tracking measurement of spontaneous vasomotion

摘要

Abstract: We developed a dynamic microvascular edge detection method which is based on an adaptive thresholding and multijudgmental criteria. To realize the on-line measurement with video rate, we first set changeable measuring lines which are perpendicular to a microvessel axis and cover the possible edge location at a cross- section of the microvessel as a sampling window. A dynamic threshold, which can frame-by-frame automatically adapt to the change of light intensity in the sampling window, will be generated based on the on-line analysis of light intensity distribution along the measuring lines. The judgment of microvascular edges is based on the pattern characteristics of the light intensity distribution curve in the microvascular edge areas and the possible range of the microvascular diameters. Multiple criteria for the edge detection were set for accurately detecting the edges and skipping the non-edge zones to speed the edge recognizing procedure. To further improve reliability of this edge detection, a dynamic graphic indicator can be generated according to the detected vessel edge location, and simultaneously displayed with the original image. This algorithm has been successfully applied for autotracking measurement of spontaneous vasomotion in microcirculation, even when the microcirculatory image had complex background and low contrast. !13