Heart Image Deformation Analysis for Quantitative Echocardiography
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Solution Overview
Problem
Existing echocardiography methods rely heavily on visual analysis by clinicians, lacking robust computer-assisted techniques for quantifying heart deformation, particularly in stress echocardiography, which hinders accurate diagnosis of conditions like coronary artery disease.
Innovation Solution
A system and method for measuring heart deformation by acquiring and processing echocardiography images to calculate parameters such as displacement, shear transformation, and principal transformation, using a decision tree for diagnostic output, supported by machine learning to analyze image data and generate diagnostic outputs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If visual analysis by clinicians is used, then diagnostic capability is maintained, but measurement precision and automation are insufficient
Solution Approach 1:
The patent replaces manual visual analysis by clinicians with an automated computer-based image processing system. The system uses digital images of the heart, applies coordinate transformations to track myocardial point movements, and automatically calculates deformation parameters (radial, circumferential, longitudinal strain) without requiring manual measurement, thereby achieving precise quantification through automation
Solution Approach 2:
The system enables self-service by allowing the computer to automatically perform all deformation measurement tasks independently. The image processing system autonomously identifies myocardial points, tracks their positions across cardiac cycles, computes deformation parameters, and generates diagnostic outputs without continuous human intervention, making the measurement process self-sufficient
2Extent of automation
If computer analysis is implemented, then automation increases, but complexity of image processing increases
Solution Approach 1:
The patent segments the complex image processing task into distinct modular stages: (1) digitizing cardiac images and identifying myocardial points, (2) applying coordinate transformations to track point movements, (3) calculating deformation parameters from position changes, and (4) generating diagnostic outputs. This segmentation reduces overall system complexity by breaking down the automated analysis into manageable, sequential processing steps
Solution Approach 2:
The patent introduces coordinate transformation as an intermediary mathematical framework that bridges raw image data and deformation measurements. By using coordinate systems and transformation equations as intermediaries, the system simplifies the complex relationship between image pixel coordinates and actual myocardial deformation, making automated calculation more tractable
Data Source
AI summary
A system for diagnosing a heart condition comprises an imaging system (102) arranged to acquire two images of the heart at respective points in the cardiac cycle, and locating means, which may be manually operated or automatic, for locating a series of pairs of points on the images. Each pair of points indicates the respective positions of a single part of the heart in the two images. The system further comprises a processor (108) arranged to calculate from the positions of said pairs of points a value of at least one parameter of the deformation of the heart. It may further be arranged to compare the value of the at least one parameter with reference data to generate a diagnostic output.