Nonlinear Beamforming Flow Processing for Ultrasound Spatial Specificity
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Solution Overview
Problem
Conventional ultrasound imaging techniques using defocused transmit beams, such as diverging or planar waves, compromise spatial specificity due to increased sidelobes and false flow signal artifacts from strong off-axis moving tissue structures, particularly in Doppler ultrasound imaging.
Innovation Solution
The method involves performing flow processing on channel data for nonlinear beamforming, which includes clutter filtering and coherence-based processing to attenuate off-axis scattering and regain spatial specificity by emphasizing phase information and coherency of moving parts, thereby reducing sidelobe energy and artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If defocused transmit beams (diverging or planar waves) are used to increase frame rates, then image acquisition speed is improved, but spatial specificity is reduced due to increased sidelobes and false flow signal artifacts
Solution Approach 1:
The patent performs flow processing on channel data before applying nonlinear beamforming. By preprocessing the channel data to extract flow information and characteristics, the system prepares the data in advance for more effective beamforming operations, enabling both high frame rates and maintained spatial specificity
Solution Approach 2:
The patent applies nonlinear beamforming that dynamically adjusts beamforming parameters based on the processed channel data. This includes adapting focus depths, aperture sizes, and weighting schemes to compensate for the defocused transmit geometry, thereby maintaining spatial specificity despite using diverging or planar wave transmission for high frame rates
2Productivity
If broader transmit beams covering wider sector are used to provide higher frame rates, then image acquisition speed is improved, but spatial specificity is significantly reduced leading to increased sidelobes
Solution Approach 1:
The patent converts the harmful sidelobe energy from defocused transmit beams into useful information by performing flow processing on channel data. The nonlinear beamforming uses the processed flow information to selectively enhance coherent signals while suppressing incoherent sidelobe artifacts, transforming what would be noise into structured, interpretable flow data
Solution Approach 2:
The patent combines multiple processing techniques into a composite approach: clutter filtering to remove stationary tissue, flow processing to extract moving blood signal characteristics, and nonlinear beamforming to coherently sum the processed channels. This composite methodology effectively manages sidelobe energy while preserving genuine flow signals
3Area of stationary object
If multiple receive lines of significant distance to transmit beam axis are deployed to procure resolved image of substantial spatial extension, then image coverage is improved, but spatial specificity is reduced
Solution Approach 1:
The patent processes channel data from multiple receive lines across the lateral dimension before applying beamforming. By performing flow processing in the channel domain and then applying nonlinear beamforming across the lateral dimension, the system effectively adds a processing dimension that restores spatial specificity for off-axis receive lines, enabling wide image coverage without sacrificing precision
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 enhances spatial specificity and increases effective image acquisition speed by eliminating MLA artifacts and improving the resolution of Doppler signals, allowing for more accurate visualization of blood flow without false signals from strong tissue scatterers.
Implementation Method 1
Doppler ultrasound imaging uses reflected sound waves to visualize blood flow through a blood vessel
Implementation Method 2
delaying the clutter filtered signals to provide delay aligned clutter filtered signals, calculating a coherency of the delay aligned clutter filtered signals, and nonlinearly combining the delay aligned clutter filtered signals and the coherency
Data Source
AI summary
Systems and methods for enhancing spatial specificity and increasing effective image acquisition speed by performing flow processing on channel data for application of nonlinear beamforming are provided. The method includes generating clutter filtered signals, delaying the clutter filtered signals to provide delay aligned clutter filtered signals, calculating coherency of the delay aligned clutter filtered signals, and nonlinearly combining the delay aligned clutter filtered signals and the coherency of the delay aligned clutter filtered signals across each transducer element at one or more depths to generate at least one beamformed signal for each received set of echo signals in a sequence of echo signals at the one or more depths. The method includes calculating and presenting a measurement for the one or more depths based on the at least one beamformed signal for each received set of echo signals in the sequence of echo signals at the one or more depths.