Cardiac anatomic structure-based left and right ventricle level set segmentation method

Abstract

The invention belongs to the technical field of medical imaging, and particularly relates to a cardiac magnetic resonance image segmentation method. A cardiac anatomic structure-based left and right ventricle level set segmentation method specifically comprises the following steps: performing geometry decomposition to a cardiac structure; resolving a convex hull of an initialized contour; producing a signaled distance function; and generating intima and extima through a dual-level set algorithm, and the like. By using the method, the simultaneous segmentation of the ventricular intima and extima and cardiac muscle can be realized, and the segmentation results can meet the physiological structure characteristics of a heart as far as possible.

Description

technical field [0001] The invention relates to the technical field of medical imaging, in particular to a method for segmenting cardiac magnetic resonance images. Background technique [0002] In the diagnosis of heart disease, medical imaging technology has become an important means of clinical examination. Among them, magnetic resonance imaging is considered the "gold standard" for noninvasive assessment of cardiac structure and function. In the analysis and processing of magnetic resonance images, accurate segmentation of cardiac anatomical structure is the basis and premise for functional analysis and disease diagnosis of the heart. However, due to the image quality problems caused by the gray scale inhomogeneity of magnetic resonance imaging, the complexity of the physiological structure of the heart and the blurring of the border caused by the heart movement, it is difficult for the classical image segmentation method to accurately segment the cardiac magnetic resona...

AI Technical Summary

Problems solved by technology

However, the current segmentation algorithm for cardiac images is mainly for the segmentation of a single cardiac structure, and there is a lack of algorithms that can simultaneously segment multiple cardiac structures, such as the simultaneous segmentation of left and right ventricles and myocardium.

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