Ultrasound Velocity Estimation via Signal Pre-processing
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Solution Overview
Problem
Vector flow imaging (VFI) ultrasound systems require high computational resources, making them costly and potentially unfeasible for implementation in existing ultrasound systems, as they need to estimate both absolute flow direction and velocity, whereas Color Flow Mapping (CFM) only provides relative flow information.
Innovation Solution
The ultrasound imaging system employs a pre-processor that basebands, averages, and decimates beamformed signals before calculating autocorrelation, reducing computational requirements by up to 30 times without losing information, allowing for the generation of axial and lateral velocity components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If VFI velocity estimator is implemented to provide absolute flow direction and velocity, then measurement precision is improved, but computational requirement increases significantly
Solution Approach 1:
The patent applies preliminary action by performing basebanding, averaging, and decimation operations on the beamformed signals before the autocorrelation calculation. This preprocessing reduces the data volume and complexity entering the velocity estimation algorithm, thereby lowering computational requirements while preserving measurement accuracy for absolute flow direction and velocity
2Measurement precision
If VFI is implemented in existing ultrasound systems, then measurement precision is improved, but cost increases due to additional computational resources
Solution Approach 1:
By performing basebanding, averaging, and decimation as preliminary processing steps before velocity estimation, the patent reduces the computational burden on the ultrasound system. This makes VFI implementation feasible in existing systems without requiring expensive high-performance computational hardware, thereby reducing overall system cost while maintaining measurement precision
3Device complexity
If computational requirements for VFI are reduced through signal processing optimizations, then device complexity is reduced, but measurement precision may be compromised
Solution Approach 1:
The patent performs preliminary averaging and decimation operations that reduce computational complexity while preserving the essential signal characteristics needed for accurate velocity estimation. The autocorrelation is then computed on this preprocessed data, maintaining measurement precision despite reduced computational requirements
Solution Approach 2:
The patent changes the parameters of the signal processing pipeline by introducing basebanding, averaging, and decimation steps that transform the raw beamformed signals into a form suitable for efficient autocorrelation-based velocity estimation. These parameter changes reduce computational complexity while maintaining the accuracy needed for precise velocity measurement
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 significantly reduces the computational burden, making VFI feasible in both new and existing ultrasound systems at a lower cost, while maintaining image quality and resolution.
Implementation Method 1
a transducer array, with an array of transducer elements that transmits an ultrasound signal and receives a set of echoes generated in response to the ultrasound signal traversing a flowing structure
Implementation Method 2
a beamformer that beamforms the set of echoes, generating a beamformed signal
Implementation Method 3
a pre-processor that performs basebanding, averaging and decimation of the beamformed signal
Implementation Method 4
a pre-processor that performs basebanding, averaging and decimation of the beamformed signal
Implementation Method 5
a decimator that decimates the averaged set of beamformed signals by a decimation factor in a range of two to eight
Implementation Method 6
an autocorrelator that determines an autocorrelation of the basebanded, averaged and decimated set of beamformed signals
Data Source
AI summary
An ultrasound imaging system includes a transducer array, with an array of transducer elements that transmits an ultrasound signal and receives a set of echoes generated in response to the ultrasound signal traversing a flowing structure. The ultrasound imaging system further includes a beamformer that beamforms the set of echoes, generating a beamformed signal. The ultrasound imaging system further includes a pre-processor that performs basebanding, averaging and decimation of the beamformed signal and determines an autocorrelation of the basebanded, averaged and decimated beamformed signal. The ultrasound imaging system further includes a velocity processor that generates an axial velocity component signal and a lateral velocity component signal based on the autocorrelation. The axial and lateral velocity components indicate a direction and a speed of the flowing structure in the field of view.