RF Blood-Flow Speed Measurement Using SVD Signal Separation
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Solution Overview
Problem
Existing methods for measuring blood flow, such as Doppler ultrasonography, skin perfusion tests, and angiography, face challenges in spatial resolution, especially for micro blood vessels and the vicinity of blood vessel walls, leading to inaccuracies and difficulties in real-time measurement.
Innovation Solution
A method involving singular value decomposition (SVD) of RF signals to classify and separate clutter, blood flow, and noise signals, followed by speckle decorrelation to measure blood flow speed, without the need for ultrasound contrast media.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Doppler ultrasonography is used to measure blood flow rate, then average blood flow rate can be measured, but spatial resolution is insufficient to measure micro blood flow or blood flow speed in the vicinity of blood vessel wall
Solution Approach 1:
The patent applies singular value decomposition (SVD) to segment the ultrasound signal into distinct components: clutter signal, blood flow signal, and noise signal. This segmentation allows separate processing of each component, enabling high spatial resolution measurement of micro blood flow while effectively removing clutter interference that would otherwise obscure the measurement
Solution Approach 2:
The patent extracts the blood flow signal from the composite ultrasound signal by identifying and isolating it from clutter and noise components through SVD. By taking out only the relevant blood flow information and removing the clutter signal, the method achieves high spatial resolution without being contaminated by surrounding tissue interference
2Measurement precision
If conventional methods are used to measure blood flow in micro vessels, then measurement can be performed, but measurement accuracy is reduced due to clutter signal interference
Solution Approach 1:
The patent converts the harmful clutter signal into a beneficial component by using SVD to identify and separately process the clutter signal. Instead of simply filtering it out, the method leverages the structured nature of clutter signals to create a clutter region mask, which is then used to guide selective signal processing that preserves blood flow information while eliminating clutter interference
Solution Approach 2:
The patent extracts and removes the clutter signal component from the ultrasound signal using SVD-based decomposition. By taking out the clutter signal and creating a separate clutter region mask, the method eliminates the harmful interference while preserving the blood flow signal for accurate speed measurement
3Measurement precision
If histological observation is used to measure blood vessels, then quantitative analysis of vascular development can be achieved, but measurement error increases due to examiner dependency and specimen preparation
Solution Approach 1:
The patent replaces manual histological observation and analysis with an automated ultrasound-based measurement system. By substituting the mechanical and manual processes of specimen preparation and examiner observation with automated signal processing and image analysis, the method eliminates examiner dependency and specimen preparation variability, achieving consistent and reliable quantitative measurements
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
Enables accurate, real-time measurement of blood flow speed in micro blood vessels and the vicinity of blood vessel walls, improving spatial resolution and reducing measurement errors.
Implementation Method 1
decomposing a complex signal converted from the RF signal into base signals using singular value decomposition
Implementation Method 2
measuring a speed of the blood flow by calculating speckle decorrelation from the output signal
Data Source
AI summary
A method of measuring a speed of blood flow from a radio frequency (RF) signal, including decomposing a complex signal converted from the RF signal into base signals using singular value decomposition, classifying the base signals into a clutter signal, a blood flow signal, and a noise signal, separating a clutter region and a blood flow region from the classified clutter signal and blood flow signal, obtaining an output signal by removing the blood flow signal from the clutter signal in the clutter region and by removing the clutter signal from the blood flow signal in the blood flow region, and measuring a speed of the blood flow by calculating speckle decorrelation from the output signal.


