Mitral Valve Motion Analysis for Cardiac Phase Identification
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Solution Overview
Problem
Conventional methods face challenges in accurately identifying end-systole (ES) and end-diastole in cardiac images, which are crucial for calculating left ventricular ejection fraction, due to difficulties in recognizing ES based on electrocardiogram signals.
Innovation Solution
An image processing apparatus and method that analyze the motion of the mitral valve by determining variations in grayscale values from target images within the endocardial contour of the left ventricle, allowing for the identification of ES and ED through the segmentation and processing of cardiac ultrasound images.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional ECG-based methods are used to identify end-systole and end-diastole, then the identification process is simple to implement, but the accuracy of end-systole identification is poor
Solution Approach 1:
The patent segments the cardiac cycle identification problem into two distinct parts: end-diastole identification using ECG R-wave detection, and end-systole identification using mitral valve motion analysis in ultrasound images. This segmentation allows each method to be optimized for its specific task, improving overall accuracy while managing complexity through division of labor between different identification approaches.
Solution Approach 2:
The patent introduces the mitral valve motion as an intermediary indicator to indirectly identify end-systole. Instead of directly detecting electrical signals, the system uses the mechanical motion of the mitral valve (observable through grayscale variations in ultrasound images) as a mediator to infer the mechanical end-systole phase, thereby improving identification accuracy through a reliable intermediate marker.
2Measurement precision
If mitral valve motion analysis is used to identify ventricular status, then the identification accuracy is improved, but the processing time increases
Solution Approach 1:
The patent extracts only the critical region containing the mitral valve from the entire cardiac ultrasound image for analysis. By focusing computational resources on this specific region of interest rather than processing the whole image, the system maintains high identification accuracy while significantly reducing processing time and computational load.
Solution Approach 2:
The patent applies partial action by analyzing only the grayscale variations in the specific region where the mitral valve is located, rather than analyzing the entire cardiac image. This partial analysis approach provides sufficient information for accurate ventricular status identification while minimizing processing time and computational resources required.
3Measurement precision
If grayscale value variations are analyzed to determine mitral valve motion, then the ventricular status can be accurately assessed, but the complexity of data processing increases
Solution Approach 1:
The patent applies local quality by focusing grayscale analysis specifically on the mitral valve region rather than the entire cardiac image. This localized approach extracts meaningful motion information from the relevant area while ignoring irrelevant regions, thereby maintaining high detection accuracy while reducing data processing complexity through selective analysis.
Data Source
AI summary
An image processing apparatus for evaluating cardiac images and a ventricular status identification method are provided. In the method, a region of interest (ROI) is determined from multiple target images, a variation in grayscale values of multiple pixels in the ROIs of each target image is determined, and one or more representative images are obtained according to the variation in the grayscale values. The target image is related to the pixels within an endocardial contour of a left ventricle. A boundary of the ROI is approximately located at two sides of a bottom of the endocardial contour. The ROI corresponds to a mitral valve. The variation in the grayscale values is related to a motion of the mitral valve. The representative image is for evaluating a status of the left ventricle.