Plaque Tissue Type Recognition Based On Image Features And Physical Features

With the aging becoming more and more serious,cardiovascular disease has become the leading disease of morbidity and mortality in China.Atherosclerotic plaque is the main cause of cardiovascular disease.Accurate classification and recognition of plaque tissue is of great significance to assist doctors in the diagnosis and treatment of cardiovascular diseases.This paper studies the recognition and classification of plaque tissue types from image features and physical features.The main contents are following:Firstly,improved region growing algorithm is proposed to improve the segmentation accuracy and realize the semi-automatic segmentation of coronary artery plaque tissue.At the same time,combined with image features(color features,texture features)and support vector machine(SVM)is used to recognize and classify different types of plaque tissue.The accuracy rate is 82.5%.Secondly,designing dynamic rheology in vitro experiment to measure the storage modulus,loss modulus and viscosity of real plaque tissue,and carrying out frequency scanning experiment,constant temperature scanning experiment and shear rate scanning experiment on plaque tissue.The experimental results show that the plaque structure is a shear thinning pseudoplastic fluid with certain elasticity and viscosity;frequency and shear rate have great influence on the stability of plaque structure;there are obvious differences between different types of plaque structure.Thirdly,the rheological characteristic curves of real plaque tissues were obtained by rheological experiments,and the physical model of plaque tissues was established by power law model.Viscosity index K and non-Newtonian index N(mean error 0.1631 and 0.0187,respectively)were proposed as characteristic parameters to classify and identify different types of plaque tissues.The accuracy rate was 86.67%.