Ultrasound Color Flow Sparkle Artifact Detection
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Solution Overview
Problem
Color flow imaging in ultrasound is susceptible to sparkle artifacts due to correlation loss in backscattered echoes, which can be indicative of underlying physiologies like kidney stones or system imperfections, and reducing gain or transmit power to mitigate this affects sensitivity.
Innovation Solution
The method involves generating color flow data at different pulse repetition frequencies, correlating these data sets to identify sparkle artifacts, and filtering the images based on similarity to maintain motion or reduce sparkle regions without compromising sensitivity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If gain or transmit power is reduced to reduce sparkle artifact, then sparkle artifact is reduced, but sensitivity is lost
Solution Approach 1:
The patent segments the color flow data into multiple datasets generated at different pulse repetition frequencies (PRFs). By dividing the data acquisition process into separate PRF passes, the system can later differentiate between true motion signals and sparkle artifacts through correlation analysis, allowing sparkle reduction without compromising sensitivity
Solution Approach 2:
The patent introduces an intermediary correlation analysis step that processes the multi-PRF color flow datasets. This intermediary processing layer enables the system to identify and remove sparkle artifacts while preserving true motion information, acting as a mediator between the raw data and the final image output
2Difficulty of detecting and measuring
If spatial variance of color flow is used to identify sparkle, then sparkle can be detected, but aliased flow or turbulence is reduced along with artifacts
Solution Approach 1:
The patent changes the parameter of pulse repetition frequency by acquiring color flow data at multiple different PRFs. This parameter variation creates distinct correlation patterns between true motion and sparkle artifacts, enabling sparkle identification through correlation analysis without relying on spatial variance that would also suppress legitimate flow signals
Solution Approach 2:
The patent creates multiple copies of the color flow data at different PRFs, then uses correlation analysis to distinguish between true motion (which maintains consistent correlation patterns across PRFs) and sparkle artifacts (which show inconsistent correlation). This copying approach enables sparkle detection while preserving flow information
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
This approach effectively detects sparkle artifacts without reducing sensitivity, allowing for clearer imaging of motion or enhancing the visibility of structures like kidney stones by distinguishing between true motion and sparkle noise.
Implementation Method 1
Color flow imaging is susceptible to artifacts when there is a loss of correlation in the backscattered echoes
Implementation Method 2
A Doppler estimator is configured to estimate, from the scanning, first motion values representing locations of the scan region and second motion values representing the locations of the scan region
Data Source
AI summary
Sparkle in color flow imaging is detected. Color flow data is estimated with different pulse repetition frequency (PRF). By correlating the color flow data estimated with different PRFs, sparkle is identified. Color flow images may be filtered to reduce motion while maintaining the sparkle region (e.g., kidney stone imaging) or reduce the sparkle region while maintaining motion (e.g., remove sparkle as system noise).