An Effective Image Measurement in Brachial Flow-Mediated Dilation Response Analysis

Non-invasive cardiovascular measurements are used to evaluate cardiovascular diseases early and to cure early. By using various evaluation methods of cardiovascular features to diagnose cardiovascular disease. Flow-mediated dilation (FMD) evaluated by ultrasound offers a mechanism to characterize endothelial function and, therefore, may play a role in the diagnosis of cardiovascular diseases. Cardiovascular endothelial is intermedia between blood and cardiovascular muscle. It has important effect for keeping balance of the environment in vessel. Nitric oxide (NO) is the most important fact. Many cardiovascular diseases, like high cholesterol, high blood pressure, coronary heart disease, diabetes, smoking, is the cause of endothelial dysfunction. We design a series of images analysis methods to compute the change of cardiovascular radius in ultrasound images for evaluating endothelial function instead of measuring by-hand. We use B-mode ultrasound system to measure brachial cardiovascular radius. Then we capture the images by image capture card 10 images per second. We evaluate the average radius of brachial cardiovascular radius before we cut off blood flow. And we evaluate the maximum radius of brachial cardiovascular radius after we cut off blood flow and release it. Using the two radii we can compute the FMD value to evaluate endothelial function. First, we use Hough transform to detect possible center possible of vessel. Then we use edge-reserved filter to filtrate speckle noise and preserve edge. After filtrating noise, we utilize Laplacian of Gaussian to detect edge-points. Finally, we use gradient-based Hough transform to determine the center position, major axis, minor axis, and angle of evaluated ellipse. We use radius of the circle witch has equal area with the evaluated ellipse to be our final result. We measure the FMD value for 8 people (age from 23 to 26 years old). Comparing the result measured by our design system with by hand, the accuracy is 96.31%