Left ventricle nuclear magnetic resonance image segmentation and three-dimensional reconstruction method

Abstract

The invention provides a left ventricle nuclear magnetic resonance image segmentation and three-dimensional reconstruction method. According to the method, a variational level set evolution model is established to be used for segmenting the boundary of the inner membrane and the outer membrane of the left ventricle, and meanwhile, a three-dimensional curved surface and entity reconstruction scheme of the left ventricle and a corresponding mesh generation scheme are also provided. Due to the fact that a novel quasi local binary simulation item based on an edge detection operator is adopted, the method can be used for effectively segmenting images which are uneven in gray level; only the area item is considered, therefore, theoretical models involved in the method can be simplified, and the algorithm operation time of the method can also be shortened; the application of the convex hull algorithm enables the method to be capable of making up the influences such as leakage caused by fuzziness of the boundary of the outer membrane. According to the method, the three-dimensional reconstruction scheme based on the contour surface generation algorithm and secondary development and application technologies of relevant commercial software is further provided, and can help a user realize three-dimensional reconstruction of the left ventricle.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a method for segmenting and reconstructing nuclear magnetic resonance images. Background technique [0002] Cardiac Magnetic Resonance (CMR) imaging can provide high-resolution images. It is one of the research hotspots in the field of medical image analysis and an important auxiliary means for the diagnosis of heart diseases. In order to make full use of the information in CMR images and provide quantitative and intuitive references for clinical diagnosis, the accurate segmentation of the intima and adventitia of the left ventricular membrane is the primary task. The left ventricular image segmentation problem mainly faces the following challenges: (1) the non-uniformity of image grayscale; (2) the adventitia border is not clear; (3) the shape of the endocardium and adventitia border in different slice images is changeable, etc. Although there are many techniques for segmenting ...

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However, Chan's active contour method cannot handle images with non-uniform grayscale well, and Li's non-reinitialization method corresponds to more gradient terms in the partial differential model, which undoubtedly increases the complexity of the model and the numerical value Calculation Amount in Discrete Solving

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