Ultrasound Doppler Peak Detection for Accurate Blood Flow Velocity
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Solution Overview
Problem
Existing ultrasound image processing methods for blood flow velocity detection, particularly in spectral Doppler modes, suffer from inaccuracies in peak detection due to errors and omissions, leading to incorrect calculation of blood flow parameters.
Innovation Solution
A method and system for ultrasound image processing that involves obtaining an ultrasound image, determining an envelope curve, identifying multiple maximum points through amplitude and time features, and correcting these points to accurately determine blood flow velocity parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If one time search is used for peak detection in Doppler waveform, then the processing speed is maintained, but the accuracy of peak detection deteriorates due to errors and omissions
Solution Approach 1:
The peak detection process is divided into multiple stages: initial peak search, peak verification, and parameter calculation. Each stage performs specific functions to progressively improve detection accuracy while maintaining manageable complexity through structured segmentation of the detection workflow.
Solution Approach 2:
The system performs preliminary peak search and identification before final parameter calculation. By conducting initial peak detection and verification in advance, the system ensures accurate peak identification is established before committing to final medical parameter computations, preventing propagation of detection errors.
2Reliability
If PRF is increased to avoid aliasing in pulsed wave Doppler mode, then the accuracy of blood flow direction detection is improved, but the risk of aliasing reappears when PRF is reduced for continuous wave Doppler mode
Solution Approach 1:
The system dynamically adjusts PRF settings based on the selected Doppler mode and detected blood flow characteristics. In pulsed wave mode, PRF is optimized to prevent aliasing while maintaining temporal resolution. In continuous wave mode, the system adapts PRF to center the blood flow signal in the spectrogram, ensuring reliable direction detection across different operational modes.
Solution Approach 2:
The system changes key parameters including PRF, baseline position, and gain settings based on the Doppler mode and blood flow characteristics. These parameter adjustments allow the system to optimize performance for each mode while preventing aliasing artifacts and ensuring accurate blood flow velocity and direction measurement.
3Productivity
If envelope detection and peak detection are performed to calculate medical parameters, then the comprehensiveness of blood flow analysis is improved, but the reliability of calculated parameters deteriorates due to peak detection errors
Solution Approach 1:
The system implements feedback mechanisms where detected peaks are verified against expected physiological patterns and envelope characteristics. Peaks that do not conform to expected patterns are flagged for re-evaluation or correction, ensuring that parameter calculations are based on accurate peak identification and reducing propagation of detection errors into final medical parameters.
Solution Approach 2:
The system performs preliminary verification of detected peaks against envelope characteristics and physiological constraints before using them for parameter calculation. This preliminary validation ensures that only accurate peaks contribute to medical parameter computation, maintaining both comprehensiveness and reliability of the analysis.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The method improves the accuracy and comprehensiveness of peak detection in ultrasound images, enabling precise calculation of blood flow velocity parameters by removing errors and supplementing missed peaks, thereby enhancing the stability and reliability of the detection process.
Implementation Method 1
the blood flow velocity may be calculated based on the Doppler effect by detecting a frequency shift of echo signals
Data Source
AI summary
The present disclosure provides a method for ultrasound image processing. at least one ultrasound image acquired by an ultrasound scan may be obtained. each ultrasound image is associated with a blood flow velocity. For each of the at least one ultrasound image, an envelope curve may be determined based on the ultrasound image; a plurality of first maximum points of the envelope curve may be determined; a plurality of second maximum points by screening the plurality of first maximum points may be obtained based on amplitude features of the plurality of first maximum points; and one or more parameters relating to the corresponding blood flow velocity may be determined based on the plurality of second maximum points.