Detection and Segmentation of Nail Fold Microcirculation Vessels based Deep-learning

Inhalt:
The state detection of nailfold microcirculation vessels is an important way for medical diagnosis of some common diseases. However, most of the parameters of nailfold microcirculation blood vessels are currently determined by artificial means. In order to achieve accurate and automatic measurement of vascular parameters, a method of detection and segmentation of nail fold microcirculation vessels based was proposed. In the process of medical diagnosis, the vascular distribution and blood circulation pathway of nailfold microcirculation were detected based on computer vision method. And the nailfold microcirculation blood vessel detection and segmentation algorithm based on deep learning technology and the centerline extraction method are used to obtain the number of blood vessels, the length of the tube loop, and the diameter of the tube loop, thereby assisting medical detection and improving the efficiency and accuracy of diagnosis.