Research On 3D Registration And Plaque Risk Judgment Algorithm Based On Multi-contrast MRI Of Carotid Artery

Stroke is an invisible blade that currently harms human health and is one of the highest causes of morbidity and mortality worldwide.Multi-contrast high-resolution magnetic resonance imaging can provide non-invasive display of wall structure and plaque composition,providing an effective means for analyzing carotid atherosclerotic plaque.By comparing and analyzing multi-contrast magnetic resonance images,it is possible to more accurately discover the presence of atherosclerosis,determine the location of plaque,judge the degree of stenosis,and identify plaque components.However,in the actual examination of magnetic resonance,because the obtained multi-contrast sequence image scan orientation and parameters are inconsistent,the geometric space is not matched,and the examination duration is prone to motion displacement.it is impossible to directly obtain accurate correspondence of carotid artery between multi-contrast images.In this paper,the three-dimensional registration algorithm is used to study the above-mentioned problems.Based on the spatial physical coordinates and the contour of the lumen,a three-dimensional registration algorithm based on multi-contrast magnetic resonance images of carotid arteries is proposed.Through the registration algorithm and the stenosis risk judgment algorithm,the carotid plaque area can be compared and detected more effectively by combining the sequence images.The main work and achievements of the thesis are as follows:Firstly,a multi-contrast MRI lumen segmentation algorithm was proposed.The algorithm uses the maximum inter-class variance segmentation result as the initial contour of the Chan-Vese model to perform continuous semi-automatic segmentation.The segmentation algorithm provided contour features for the three-dimensional registration algorithm and the parameters for subsequent stenosis judgment algorithms.Secondly,a multi-contrast MRI three-dimensional registration algorithm basedon spatial alignment and contour matching was proposed.The algorithm used the physical coordinates of the image to perform the inter-layer alignment of the spatial position.The three-dimensional point cloud composed of lumen contour was used to perform three-dimensional registration based on the improved iterative closest point algorithm.The algorithm achieved three-dimensional accurate registration of carotid artery in multiple contrast magnetic resonance images,which would lay a foundation for the analysis of the components of subsequent vulnerable plaques.Finally,based on lumen segmentation and three-dimensional registration algorithm in multi-contrast MRI,a risk assessment algorithm for carotid stenosis was proposed.The algorithm mainly utilized the carotid artery display of multi-contrast MRI and quantitatively analyzed the region between lumen and wall to accurately determine the degree of arterial stenosis and then quantitatively analyze the vulnerable plaque components.In this paper,the multi-contrast MRI of carotid artery was focused on and a three-dimensional registration and plaque risk judgment algorithm based on carotid multi-contrast MRI was proposed.The three-dimensional registration of multi-contrast MRI was performed by accurately segmenting the contour of carotid artery lumen,thereby obtaining the rate of carotid stenosis and quantitative analysis of plaque components in order to accurately determine the risk of plaque.Subsequent studies will improve the current method and apply more patient data to quantify the atherosclerotic plaque while validating the effectiveness of this algorithm.