Cardiac-Cycle Signal Extraction from Echocardiogram Data
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Solution Overview
Problem
Current methods for extracting cardiac-cycle information from echocardiograms are computationally intensive and not robust, relying heavily on spatial processing to identify reference points, which can be time-consuming and imprecise, especially in situations where ECG electrodes cannot be attached, such as in emergency contexts.
Innovation Solution
A method that generates a cardiac-cycle signal by resizing echocardiogram frames, creating a matrix from flattened image frames, and deriving a unitary matrix with singular vectors to produce a cardiac-cycle signal without the need for complex image processing, relying on temporal information rather than spatial information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If spatial processing methods are used to identify reference points in echocardiogram frames, then cardiac-cycle information can be extracted, but the process becomes computationally intensive and time-consuming
Solution Approach 1:
The patent extracts only the essential temporal information from echocardiogram frames by converting spatial image data into temporal signals through matrix operations and singular value decomposition. Instead of processing entire spatial frames to identify reference points, the method extracts cardiac-cycle information directly from the temporal variations in the image sequence, significantly reducing computational burden while maintaining extraction accuracy.
Solution Approach 2:
The patent replaces complex spatial image processing mechanisms with mathematical matrix operations and singular value decomposition. Instead of using traditional spatial filtering and reference point detection algorithms, the method uses linear algebra operations on flattened image frames to extract cardiac-cycle signals, substituting mechanical spatial processing with computational mathematical transformations that are faster and more efficient.
2Measurement precision
If complex image processing is used to extract cardiac information from echocardiograms, then more accurate results can be obtained, but the device complexity increases
Solution Approach 1:
The patent changes the parameter representation of echocardiogram data from spatial image coordinates to temporal signal parameters through matrix transformation. By converting 2D spatial frames into 1D temporal signals using singular value decomposition, the method simplifies the processing parameters while maintaining the essential cardiac information, reducing device complexity without sacrificing extraction accuracy.
Solution Approach 2:
Instead of processing spatial information to extract temporal cardiac signals (the traditional approach), the patent inverts the approach by directly extracting temporal signals from the temporal variations in the image sequence through matrix operations. This inversion eliminates the need for complex spatial processing algorithms while maintaining measurement precision.
3Measurement precision
If ECG electrodes are attached to obtain cardiac timing information, then accurate heart rate and phase information can be obtained, but the procedure becomes laborious and unsuitable for emergency contexts
Solution Approach 1:
The patent makes the echocardiogram device multi-functional by enabling it to extract both anatomical imaging information and temporal cardiac signals from the same ultrasound data. Instead of requiring separate ECG equipment and electrode placement, the ultrasound system itself performs cardiac-cycle signal extraction through matrix operations on the acquired image frames, providing universal functionality that simplifies operation in emergency contexts.
Solution Approach 2:
The echocardiogram system performs self-service by extracting its own cardiac timing information from the ultrasound images it already captures. The system uses its acquired image data to generate cardiac-cycle signals through singular value decomposition, eliminating the need for external ECG equipment and making the procedure self-sufficient, particularly valuable in emergency situations where rapid assessment is needed without additional equipment setup.
Data Source
AI summary
The present approach relates to extracting a heart cycle signal from ultrasound sequences (e.g., echocardiograms) without complex spatial image processing and without finding or assuming the knowledge of the position of heart reference points. The present heart cycle signal is computed by determining temporal changes in low-resolution versions of the echocardiographic frames, such as temporal information of the heartbeat.