Dynamické sledování a evaluace geometrických vlastností cévního systému v závislosti na tlakovém namáhání

Abstract

The aim of this diploma thesis is the design of automated procedures for the detection of geometric parameters from a video signal and modeling the dynamics of the vascular system during compressive stress. Within the analysis, two variable approaches for the detection of objects of interest from video are discussed. It is an algorithm that detects aortic thickness based on color markers and a method that allows monitoring the distribution of aortic thickness along its entire length, including other geometric parameters that are implemented in MATLAB. Subsequently, these methods are compared in order to evaluate the efficiency of algorithms. Furthermore, the efficiency of image preprocessing in the case of the aortic thickness distribution model is evaluated. In addition to presenting the development of the algorithm, this work describes the mechanical properties of the vascular system, the principles of monitoring geometric properties or algorithms for parameter extraction. Subsequently, signal analysis is performed to test the significance of signal variability for aortic variable regions and statistical analysis, including descriptive statistics, two-sample testing of median values using the Wilcoxon test, and multi-sample testing performed by the Kruskal-Wallis test