Microcirculation And Myocardial Cell Microscopic Image Characteristic Parameters Of Dynamic Measurement Technology And Applied Research

Cardiovascular system is the motor system of maintaining basic vital movement. Autorhythmic systole/diastole changes (Vasomotion) are ubiquitous in the movements of heart, microvasculars and microlymphtics. Vasomotion is the energy source of tissue and organ perfusion. The autorhythm of circulation system is becoming one of the most hot spots of medical research.Cardiomyocyte is basic cardiac contractive functional unit on pumping blood. Dynamically analyzing the pulsation property of cultured cardiomyocyte possesses important significance on detecting the rule of autorhythmic movement and probing the pathogenesis of cardiovascular disease. The system of microcirculation which combined from microvasculars, microlymphtics and humour is critical part of circulatory system, and the main place of oxygen, nutrients, signaling molecules exchanging. Vasomotion of microvasculars and microlymphtics can not only adjust humoural stream but also afford energy to wavelike tissue perfusion.Vasomotion is a dynamic process versus time changes. A series of image sequence need to be analyzed to extract the characteristic parameters. High-speed, accurate automated dynamic measuring technology of characteristic parameters is the research foundation of biothythm. Because of limitations on the research techniques, some valuable indexes are difficult to extract, even can not be extracted at present. The objective of this research is proposing creative technical supports for autorhythmic activitiy studies.This study focused on measuring methods of characteristic parameters of static images and dynamic cardiomyocyte beating videos, autorhythmic microcirculation videos. Automated method was developed for extracting and measuring characteristic parameters of microvasculature. We also developed a dynamic, multi-parameter synchronous measuring method to study cardiomycyte autorhythmic activities in videos. This novel method has been used in the studies of mechanical parameters of cardiomycyte pulsation, and discovered some new phenomenon. In order to study on microcirculation vasomotion videos, we proposed a novel automated method to dynamically tracking and determining microlymphtic and microvascular diameters.Measurement of characteristic parameters in static images is the foundation of that in dynamic videos. At first, we analyzed the difference of gray degree between microvasculature and background of each color channel of colorful static microvascular images. The result shows that the channel G possessed the highest contrast, suggesting that channel G is the most adaptive arm for image processing. Single traditional algorithm of image segmentation cannot precisely extract vessel region from muscle tissue images with complex background. The result often bigger than true value, because of much background was misrecognized as vessel. We proposed a novel method called "TPSP segmentation algorithm" to overcome this obstacle. Channel G was choose to as processing arm. After noise filtering and image enhancing, image matrix was firstly segmented by threshold algorithm, morphological filtered to split vessel and remained background. Seed fill algorithm was employed to recognize the arm vessel region. Morphological filtered employed again to fill the lacunas caused by leukocytes and transparent plasma layer. And edges were smoothed by median filter. Finally, we realized the precise vasculature segmentation from muscle tissue images with complex background. Vascular density was calculated based on foregoing segmentation. Further more, we improved the burdensome manual measuring method of tortuosity and vascular density to be semi-automated, which can advance the speed of measurement.Autorhythmic cardiomyocytes are basic functional units. Because of the obstacle of lack of appropriate technology, studies of cardiomyocyte pulsatile activity mainly focus on frequency and intracellular electronic signal changes. In this study,"vector template auto-tracking algorithm " was employed to tracking the movement of arm point on cell surface. Not only can dynamically measure the frequency which can be determined by eyes, but also can measure mechanical parameters such as displacement, amplitude, velocity and acceleration which cannot be determined by eyes. Further more, we used this novel method to track the autorhythmic pulsation of48h cultured cardiomyocytes extracted from different part of neonatal SD rats. Result shows that there are significant statistic differences not only in constriction frequency but also in constriction amplitude, velocity and acceleration.Dynamic diameter changes of microvascular and microlymphtic is foundation of vasomotion research. Image sequence of microcirculation videos having the properties of image shifting and blur edges. In order to correct the error caused by image shifting, we employed feature tracking algorithm of moving objective to get the shift vector first. And then, adjust the position sample line according to the shift vector. We marked the initial edges and edge templates in the first image frame, and employed automated matching searches of edge features to track edge position changes dynamically. This a series of image processing makes we overcame obstacles in edge recognizing,edge tracking, and implemented the dynamic diameter tracking and measuring of microvasculars and microlymphtics.1. A novel image segmentation method-"TPSP segmentation algorithm" was proposed to extract vasculature from images which taken from muscle tissues. Vascular density was calculated based on segmentation. This method can significantly advance the speed of measurement. Image matrix was firstly segmented by threshold algorithm, morphological filtered to split vessel and remained background. Seed fill algorithm was employed to recognized the arm vessel region. Morphological filtered employed again to fill the lacunas caused by leukocytes and transparent plasma layer. And edges were smoothed by median filter. Finally, we realized the precise vasculature segmentation from muscle tissue images with complex background.2. We improved the burdensome manual measuring method of tortuosity and vascular density to be semi-automated, which can advance the speed of measurement.3."Vector Template Auto-tracking Algorithm" was employed to tracking the movement of arm point on cell surface. This method can measure mechanical parameters such as displacement, amplitude, velocity and acceleration which cannot be determined by eyes.4. Constriction velocity and acceleration were proposed as new indexs to evaluate constriction function of cultured cardiomyocytes. These indexs possess more coherence with clinical diagnosis on cardiac constriction function.5. We used the novel method to track the autorhythmic pulsation of48h cultured cardiomyocytes extracted from different part of neonatal SD rats. Result shows that there are significant statistic differences not only in constriction frequency but also in constriction amplitude, velocity and acceleration.6. In order to correct the error caused by image shifting, we employed feature tracking algorithm of moving objective to get the shift vector first. And then, adjust the position sample line according to the shift vector.7. We marked the initial edges and edge templates in the first image frame, and employed automated matching searches of edge features to track edge position changes dynamically. This a series of image processing makes we overcame obstacles in edge recognizing,edge tracking, and implemented the dynamic diameter tracking and measuring of microvasculars and microlymphtics.