| As the world’s population ages,atrial fibrillation(AF)has risen to a high incidence in cardiovascular and cerebrovascular diseases.Left atrial appendage(LAA)is the main site for the formation of cardiogenic thrombosis in patients with AF.The thrombi fall off and drift along blood to the brain.Cerebral vascular occlusion caused by thrombi may lead to stroke.Stroke has the characteristics of high incidence,high disability rate,high mortality rate,high recurrence rate and high economic burden,which seriously endangers the quality of life and health of human beings.In order to evaluate the risk of cardiac thrombi formation and exfoliation effectively,the research of LAA cavity segmentation and intracavitary substance automatic detection based on cardiac CT are focused in this paper.It mainly includes the following four aspects:· Single-phase segmentation of the LAA.In view of the strong correlation between the complex and changeable morphology of the LAA and its associated lesions,the “FCN+ improved CRF” method was introduced to eliminate the interference of adjacent tissues and organs and to precisely segment single-phase LAA.Based on the segmentation results,the basic model is provided for its neck modeling;the initial foreground and background seed points are provided for its multi-phase segmentation;and the selection spaces of all tracked voxels are provided for its intracavitary substance detection.· Neck modeling of LAA.Aiming at the problem of high risk of LAA occlusion,an adaptive algorithm based on optimization is proposed to realize the automatic neck modeling of LAA before operation,which can help to select the type,style and specification of occluder.By establishing the standard coordinate system and measurement of the support tension of the closure at each point of the neck,the implanted position and posture of the occluder are determined in advance.So as to develop a reasonable surgical plan,assisted closure operation.· Multi-phase segmentation of the LAA and automatic diagnosis of AF.The LAA is a constantly deforming tissue,single-phase segmentation results are not enough to reflect the true shape of the LAA,hence an 3D Graph-cut approach with time and space continuity is proposed to automatically select the foreground and background seed points,which is used to segment multi-phase LAAs in a entire cardiac cycle.This batch processing improves segmentation efficiency and performance.The multi-phase segmentation results provides a stable imaging basis for subsequent LAA function analysis and disease diagnosis.Aiming at the diagnosis of AF for conventional dynamic electrocardiogram can not directly reflect the functional changes of the LAA during AF,the seven key functional indices of LAA are estimated by volume change ratios based on the results of multi-phase segmentation result.Furthermore,the quantitative diagnosis of AF and the risk assessment of LAA thrombosis are achieved by constructing the SVM classifier and multivariate logistic regression analysis algorithm.· Automatic detection and diagnosis of substances in the LAA.In view of the fact that LAA thrombosis is the direct cause of stroke,it is of great clinical significance to detect and analyze the substances in the LAA.A approach based on timefrequency features to analyze the 3D motion trajectories of intracavitary voxels is proposed.This approach includes constructing a thrombus recognition model based on a discrete-time Fourier transform and performing singularity detection of thrombi signals based on wavelet transformation.The final results included: normal blood morphology;abnormal morphology of mild,moderate and severe SEC;location,shape,size and texture of different types of thrombus;age of thrombus:initial jelling,calcified,organic;the risk of thrombi falling off;and the average load of the thrombi in the cavity.The proposed approach based on voxel level can be extended to the detection and diagnosis of other moving tissues or organs. |
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