Ultrasound Probe Calibration via Angular Error Compensation
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Solution Overview
Problem
Ultrasound probes experience mechanical alignment errors during assembly, leading to distortion in 3D ultrasound data, which affects accurate measurement of body features like bladder volume and organ dimensions, with existing phantom variability tests providing neither precise nor quantitative error estimates.
Innovation Solution
A method involving a target with a repetitive pattern for calibrating ultrasound probes, estimating and compensating for angular errors using a simplified error model, and applying offset parameter values to generate distortion-free images, either through mechanical or software adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If mechanical assembly is performed during probe manufacturing, then the probe can be constructed and operated, but mechanical alignment errors occur leading to distortion in 3D ultrasound data
Solution Approach 1:
The calibration process is performed before the probe is deployed for actual ultrasound measurements. A target with known geometric features is imaged first, allowing calculation of transformation parameters that compensate for mechanical alignment errors. This preliminary calibration step ensures that subsequent measurements are accurate despite manufacturing tolerances.
Solution Approach 2:
The system changes the parameter space by introducing transformation parameters (rotation and translation) that map between the target coordinate system and the probe coordinate system. By adjusting these parameters based on calibration data, the system compensates for mechanical alignment errors without physically reassembling the probe.
2Reliability
If existing phantom variability tests are used to check distortion, then some quality control is provided, but precise and quantitative error estimates are not obtained
Solution Approach 1:
The system replaces subjective visual inspection of phantom images with automated image processing and mathematical analysis. Transformation parameters are calculated objectively by comparing the imaged target features with their known geometric definitions, providing quantitative error estimates rather than qualitative assessments.
Solution Approach 2:
A mathematical transformation model serves as an intermediary between the physical phantom and the evaluation criteria. The model provides a precise coordinate system mapping that enables quantitative measurement of distortion by comparing transformed target coordinates with expected values, yielding precise error estimates for probe alignment.
3Measurement precision
If complex calibration procedures are implemented to achieve high precision, then measurement accuracy improves, but device complexity and calibration time increase
Solution Approach 1:
The calibration procedure is segmented into distinct, manageable steps: imaging the target, identifying target features in the image, calculating transformation parameters, and applying corrections. This segmentation makes the calibration process systematic and automatable, reducing complexity while maintaining precision.
Solution Approach 2:
The system performs self-calibration by automatically processing the images and calculating transformation parameters without requiring manual measurement or complex user intervention. The automated image processing and parameter calculation reduce the complexity burden on the user while achieving high measurement 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
Enables precise visualization and analysis of spatial distortion in 3D volume data, providing accurate probe output by compensating for mechanical alignment errors, thus improving measurement reliability.
Implementation Method 1
An ultrasound probe typically includes one or more ultrasound transducer elements that transmit ultrasound energy and receive acoustic reflections or echoes generated by internal structures/tissue within a body
Data Source
AI summary
A method for calibrating an ultrasound probe includes receiving, from the ultrasound probe, data of a target within a test fixture, wherein the target includes a repetitive pattern along two axes; generating a first ultrasound image of the target; and identifying distortion of the target in the first ultrasound image. The method also includes estimating, based on identifying the distortion, offset parameter values for one or more of three angular errors within the ultrasound probe; generating a second ultrasound image of the target using the offset parameter values; identifying corrected distortion of the target in the second ultrasound image; and storing the offset parameter values.