Cardiac medical image processing method, processing device, processing system and medium

Abstract

The invention relates to a cardiac medical image processing method, a processing device, a processing system and a medium. The method comprises the following steps: receiving a cardiac medical image of a left ventricle long-axis section; utilizing the trained first learning network to identify mitral valve base points and apex apexes on two sides of the left ventricle and the outer edge and the inner edge of the left ventricle myocardium; arranging an upper edge by utilizing a first connecting line of a mitral valve base point; defining the left ventricular myocardium by the upper edge, the inner edge and the outer edge, using the midpoint of the first connecting line and the second connecting line of the apex of the left ventricular as the midline, evenly dividing the parts, on the two sides of the midline, of the left ventricular myocardium into n parts, and therefore the left ventricular myocardium is divided into 2n sections. According to the cardiac medical image processing method, the processing device, the processing system and the medium, each cardiac muscle area can be automatically, accurately and quickly drawn and identified, the workload of doctors is greatly reduced, and automatic identification of the cardiac medical image processing device can continuously benefit from a training data set marking the cardiac muscle areas through training.

Description

technical field [0001] The present disclosure generally relates to image processing and analysis. More specifically, the present disclosure relates to a processing method, a processing device, a processing system and a medium for cardiac medical images. Background technique [0002] The traditional parameter for evaluating overall myocardial function is mainly left ventricular ejection fraction. This single-dimensional parameter cannot comprehensively evaluate the overall myocardial function, let alone accurately reflect the diastolic and contractile movements of the local myocardium. Damage is often a gradual process from local to overall. [0003] Myocardial strain (MS) refers to the deformation of the myocardium during the cardiac cycle, which refers to the percentage change of the size of the myocardium in a certain dimension relative to the initial myocardial length or the state of no stress, and can be used to interpret the elongation of the myocardium Or shorten, th...

AI Technical Summary

Problems solved by technology

Due to the semi-automatic operation, the instrument cannot automatically identify the myocardial area, and the doctor needs to manually outline it in the first frame of the image. At the same time, the instrument’s built-in outline curve tracking function cannot accurately outline the edge of the myocardial area in the subsequent dynamic video, so it cannot be accurately detected. Change track of myocardial speckle

It is necessary to select several pairs of myocardial spots and detect their average trajectory to calculate the myocardial strain rate. However, for patients with non-uniform myocardial thickness such as hypertrophic cardiomyopathy, only the distance change between limited pairs of myocardial spots cannot truly reflect the overall myocardial strain rate. deformation

Furthermore, the shape of myocardial speckles in each frame of image is not exactly the same, and there are often some changes, and even some myocardial speckles may not appear in some frames, which brings difficulties to tracking

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