Study Of Microvascular Diameter Measuring And Blood Flow Tracking And Measuring In Conjunctival Image

The diameter of the bulbar conjunctiva micro blood vessel and the velocity of blood flow are the two vital indexes to reflect the situation of human micro-circulation, and medical studies have shown that changes in capillary diameter and flow rate with cardiovascular and cerebrovascular diseases, diabetes has a direct relationship.Image analysis based methods to automatically measure these two indexes are the essential ways of the human microcirculation analysis, though they appear to be the form of physical parameters. Research shows that those parameters provide a potential aspect for clinical diagnosis. In addition, they are also instrumental in revealing the drug mechanism, improving drug efficacy and fastening new drug development. The most important perspective is to understand the subtle operation mechanism of tissues and organs, and even find induced lesions.This paper briefly introduced the research significance and status of bulbar conjunctiva micro blood vessel image processing. Then a thorough investigation was launched to automatically measure the diameter and blood flow of bulbar conjunctiva micro blood vessels with the help of microscopic image processing. Some novel algorithms were proposedand complete the appropriate method validation experiments. Major contributions of this dissertation include:The calibration of microscopic imaging system was studied to overcome imaging system geometry uncertainty caused by the position changes of the camera in the process of the bulbar conjunctiva microscopic image acquisition. Firstly, methodologies of conjunctiva microscopic image acquisition were investigated. After that, a lighting apparatus was designed to facilitate the micro vascular image acquisition. Finally, the surface standard circular correction and scaling method was introduced.Based on the characteristic analysis of bulbar conjunctiva microscopic images, the K-SVD noise removal method was proposed using the sparse matrix and the over-complete dictionary. The experimental results demonstrated that this algorithm can effectively suppress noise while preserving detailed information. By comparing with the median-Wiener filter and Gabor filter, the proposed method outperforms the above two methods.Targeting the problems of unclear blood vessel boundaries, the cluster segmentation was proposed to calculate the diameters of micro blood vessel using intervals of successive iteration. This algorithm can effectively detect the contours of micro blood vessels.Inside the micro blood vessels, the blood flow exhibits typical non Newtonian fluid characteristics. As a result, blood cells aggregate non-uniformly and overlap each other. To solve the problem of cell tracking, the variation level set method was proposed and the blood flow velocity was estimated based on iterative Randon transform.