Flow Acceleration Estimation from Beamformed Ultrasound Data
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Solution Overview
Problem
Existing methods for estimating flow acceleration from ultrasound data are highly sensitive to noise in velocity estimates, leading to increased noise levels in acceleration measurements, which complicates clinical evaluations and requires invasive procedures.
Innovation Solution
A method and apparatus that directly estimate flow acceleration from beamformed ultrasound data using a flow acceleration processor, which extracts specific data subsets and applies double cross-correlation to generate a signal indicative of flow acceleration, independent of velocity estimates, thereby reducing noise transfer and allowing for more accurate acceleration estimation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If flow acceleration is estimated by differentiating velocity estimates, then flow acceleration can be derived for clinical evaluation, but noise in velocity estimates is amplified leading to high noise levels in acceleration measurements
Solution Approach 1:
The patent segments the velocity estimation process into multiple discrete velocity estimates at different time points, then applies differential quotient calculation to these segmented estimates. This allows the acceleration to be derived from distinct velocity measurements rather than continuous differentiation, reducing noise amplification while maintaining measurement precision.
Solution Approach 2:
The patent performs preliminary velocity estimation and filtering before acceleration calculation. By pre-processing the velocity data through careful estimation and optional filtering, the noise content is reduced before the differentiation step, preventing noise amplification in the final acceleration measurements.
2Measurement precision
If differential quotient is used to calculate acceleration from velocity, then acceleration can be derived, but the mathematical operator performs high pass filtering that increases noise levels
Solution Approach 1:
The patent introduces an intermediary step between velocity measurement and acceleration calculation. Instead of direct differentiation, it uses discrete velocity estimates at multiple time points as intermediaries, allowing the acceleration to be derived through a controlled differential quotient calculation that limits noise amplification while maintaining derivation accuracy.
3Reliability
If filtering and least squares analysis are used to reduce noise, then noise levels can be managed, but the device complexity and processing requirements increase
Solution Approach 1:
The patent applies partial filtering and selective least squares analysis only where necessary, rather than comprehensive processing of all data. By applying noise reduction techniques selectively to specific velocity estimates or time points, it achieves adequate noise control without the full complexity of continuous filtering and modeling across the entire dataset.
Data Source
AI summary
A method for determining a flow acceleration directly from beamformed ultrasound data includes extracting a sub-set of data from the beamformed ultrasound data, wherein the sub-set of data corresponds to predetermined times and predetermined positions of interest, determining the flow acceleration directly from the extracted sub-set of data, and generating a signal indicative of the determined flow acceleration. An apparatus includes a beamformer (112) configured to processes electrical signals indicative of received echoes produced in response to an interaction of a transmitted ultrasound signal with tissue and generate RF data, and an acceleration flow processor (114) configured to directly process the RF data and generate a flow acceleration therefrom.