Ultrasound Attenuation Coefficient Estimation via Frequency Power Ratio Curve Smoothing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing ultrasound attenuation coefficient estimation (ACE) methods face challenges in accurately estimating attenuation coefficients due to frequency power ratio curve oscillations caused by signal interferences and non-uniform tissue structures.
Innovation Solution
The method involves accessing ultrasound data from a subject, detecting non-uniform structures, generating frequency power ratio curve data by reducing contributions from these structures, and then estimating attenuation coefficient data using a computer system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional ultrasound ACE methods are used, then the measurement process is simple, but the measurement precision is poor due to frequency power ratio curve oscillations
Solution Approach 1:
The patent divides the ultrasound data into multiple subsets with different characteristics (e.g., different transmit/receive apodizations, focusing methods, or signal processing parameters) and processes each subset separately. This segmentation allows the system to identify and exclude problematic data portions that cause oscillations while retaining useful information from other subsets, thereby improving measurement precision without requiring complete redesign of the entire processing system.
Solution Approach 2:
The patent extracts and removes specific portions of ultrasound data or specific frequency components that are responsible for generating oscillations in the frequency power ratio curve. By identifying and taking out these harmful components (such as data from regions with non-uniform structures or artifacts), the system can generate cleaner attenuation coefficient estimates while maintaining the overall simplicity of the measurement process.
2Measurement precision
If all ultrasound data is processed without filtering, then the productivity is high, but the measurement precision is reduced due to oscillations from non-uniform structures
Solution Approach 1:
The patent applies different processing quality levels to different regions or subsets of the ultrasound data. Instead of uniformly processing all data with high complexity, the system identifies local regions with non-uniform structures or artifacts and applies enhanced filtering or exclusion only to those specific regions. This local quality approach maintains high productivity for uniform regions while ensuring high precision for problematic areas.
Solution Approach 2:
The patent performs partial processing by selectively processing only the portions of ultrasound data that are most critical for accurate attenuation measurement, rather than processing all data equally. This partial action approach allows the system to maintain high productivity by skipping unnecessary processing steps for low-quality data while ensuring thorough processing for high-quality data segments.
3Measurement precision
If frequency power ratio curve oscillations are reduced through data averaging, then the measurement precision improves, but the loss of time increases due to additional processing steps
Solution Approach 1:
The patent performs preliminary actions by pre-organizing and pre-characterizing ultrasound data subsets before the main attenuation coefficient calculation. By pre-sorting data based on quality metrics and pre-identifying problematic regions, the system can quickly exclude unwanted data during the main processing step without requiring time-consuming analysis at that stage, thereby reducing overall processing time while maintaining precision.
Solution Approach 2:
The patent implements a strategy to skip or rush through the processing of known problematic data portions. By having pre-identified which data subsets are likely to cause oscillations (through preliminary quality assessment), the system can quickly exclude these portions without performing full analysis on them, thereby reducing the time required to achieve stable frequency power ratio curves.
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 results in more accurate ACE measurements by reducing oscillations in frequency power ratio curves, allowing for improved clinical applications such as fatty liver detection and assessment.
Implementation Method 1
Ultrasound data acquired from a subject with an ultrasound system are accessed with a computer system
Data Source
AI summary
Ultrasound attenuation coefficient estimation (“ACE”) techniques that can ameliorate frequency power ratio curve oscillations caused by signal interferences, non-uniform tissue structures, or both, are described. The resulting smoothed frequency power ratio curves enable more accurate ACE and reduced region-of-interest (“ROI”) sizes for linear regression.