Shear Wave Elastography Using RANSAC Outlier Filtering
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Solution Overview
Problem
Current shear wave elastography methods face challenges in obtaining precise velocity and elasticity parameter estimates, particularly due to outliers and limited resolution, which affects the accuracy of tissue characterization in medical imaging.
Innovation Solution
The method involves acquiring B-mode ultrasound images, selecting a region of interest, transmitting focused shear wave excitation pulses, measuring displacements at multiple tracking focal points, determining displacement curves over time, and using the RANSAC algorithm to find the best fitting regression line for accurate velocity and elasticity parameter calculation, while filtering out outliers and enhancing resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional linear regression is used to estimate shear wave velocity from displacement data, then the calculation process is simple, but the measurement precision is reduced due to outliers affecting the regression accuracy
Solution Approach 1:
The patent extracts and removes outlier data points from the displacement measurements before performing regression analysis. By identifying and eliminating anomalous data that would otherwise skew the velocity estimation, the RANSAC algorithm ensures that only reliable measurements contribute to the final velocity calculation, thereby improving measurement precision without requiring complex alternative regression methods
Solution Approach 2:
The RANSAC algorithm implements an iterative feedback mechanism where initial velocity estimates are used to identify outliers, which are then removed to generate improved velocity estimates. This iterative process continues until convergence, with each cycle providing feedback that refines the velocity estimation by eliminating increasingly accurate outlier identifications, thereby progressively improving measurement precision
2Reliability
If shear wave excitation pulses are transmitted outside the region of interest, then the shear wave propagation can be monitored in the target area, but the reliability is reduced due to potential overlap with tracking pulses and azimuthal translation issues
Solution Approach 1:
The patent performs preliminary planning of the excitation pulse transmission location and timing before actual measurement. By pre-determining the optimal excitation position outside the region of interest and calculating the appropriate time delays for tracking pulses, the system avoids potential overlaps and azimuthal translation issues during actual operation, thereby ensuring measurement reliability without requiring complex real-time adjustments
Solution Approach 2:
The patent introduces an intermediate excitation region that serves as a buffer zone between the tracking region and the actual tissue of interest. By placing the shear wave excitation source in this intermediate area outside the region of interest, the generated shear waves propagate through the intermediate zone into the target area, allowing monitoring without direct excitation interference in the measurement region, thereby improving reliability while managing transmission control complexity
3Measurement precision
If multiple tracking focal points are used to measure displacements, then the resolution of velocity estimation is improved, but the quantity of data to be processed increases
Solution Approach 1:
The patent segments the region of interest into multiple tracking focal points along laterally staggered tracking lines, allowing displacement measurements at different spatial locations. By dividing the measurement space into discrete segments (focal points), the system captures spatial variations in shear wave propagation, improving velocity estimation precision through multi-point measurements while organizing data in a structured manner that facilitates efficient processing
Solution Approach 2:
The patent uses a sufficient number of tracking focal points to achieve the required measurement precision without unnecessarily increasing data volume. By selecting an optimal number of focal points that provides adequate spatial sampling for accurate velocity estimation, the system avoids both undersampling (which would reduce precision) and oversampling (which would unnecessarily increase data processing requirements), thereby balancing precision improvement with data management efficiency
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 provides more precise and reliable estimates of shear wave velocity and elasticity parameters, improving tissue characterization and aiding in more effective diagnosis by offering a direct and intuitive visual representation of tissue properties.
Implementation Method 1
Due to the effect of the acoustic radiation force of the excitation pulses, the tissue in the excitation target region is displaced simultaneously establishing a shear wave
Implementation Method 2
Monitoring the shear waves is carried out by tracking pulses transmitted in the region of interest and the corresponding reflected echoes measures the displacements of the tissues
Data Source
Figure 1A~1B
Figure 1C
Figure 2
AI summary
Method for shear wave elasticity imaging comprising the following steps: a) acquiring B-mode ultrasound images of a target region in a body under examination; b) selecting a region of interest inside the said B-mode image; c) transmitting a shear wave excitation pulse focalized on an excitation region; d) measuring the displacements of a certain number of tracking focal points or depth ranges at different depths positions along each one of a predefined number of laterally staggered tracking lines within the selected region of interest; e) determining a curve representing the displacement of the tissue as a function of time at different spatial locations within the region of interest; f) determining for each said spatial locations in the region of interest the time of arrival of the shear wave at the said spatial location by setting as the time of arrival of the shear wave as a function of the curve representing the displacement of the tissue as a function of time; g) finding the linear functional relation between the time of arrival and the spatial coordinate in the said lateral direction, i.e. in the direction of propagation of the shear wave perpendicular to the direction of the tracking lines, which linear function best approximates the determined time of arrivals at the positions of the tracking lines along the said lateral direction; h) determining the inverse of the velocity of the shear wave in a spatial location as the angular coefficient of the said linear function in a coordinate system representing the time of arrival along the y-coordinate and the position along the lateral direction at which the time of arrival has been recorded on the x-coordinate, i.e. the slope of the straight line representing the said linear function in the said coordinate system, and which method further comprises the following steps: i) step f) is carried out by considering as time of arrivals the time related to each local maxima of the displacement curve at the corresponding spatial location, and j) step g) is carried out by determining the linear function best fitting the said data pairs of local maxima of the displacement and related time of arrival applying a Random Sample Consensus algorithm (RANSAC algorithm).