Liver ROI Segmentation for Precise Shear-Wave Elastography
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Solution Overview
Problem
Current methods for diagnosing non-alcoholic fatty liver disease (NAFLD) are invasive and prone to sampling errors, and non-invasive alternatives like ultrasound imaging lack precision in identifying regions of interest for shear-wave elastography.
Innovation Solution
An ultrasound imaging system that automatically identifies and segments regions of interest in the liver for shear-wave elastography by filtering out non-liver tissue, blood vessels, and poor probe contact artifacts, and provides real-time indicators for probe positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual identification of region of interest is used in shear-wave elastography, then operator flexibility is maintained, but measurement precision and consistency deteriorate due to human error and variability
Solution Approach 1:
The system performs automatic region of interest identification through multi-mask image processing, allowing the imaging system to identify and segment relevant liver tissue regions autonomously without requiring manual operator intervention, thereby improving measurement precision while maintaining manageable system complexity through algorithmic automation
Solution Approach 2:
The manual mechanical process of operator-based region identification is replaced with an automated digital image processing system that uses multiple masks (liver tissue mask, poor probe contact mask, axial distance mask, lateral distance mask) to automatically identify and segment the region of interest, eliminating human variability while maintaining system complexity within acceptable limits
2Measurement precision
If liver biopsy is performed for NAFLD diagnosis, then diagnostic accuracy is improved, but patient comfort and procedure simplicity deteriorate due to invasiveness
Solution Approach 1:
The invasive mechanical biopsy procedure is replaced with non-invasive ultrasound-based shear-wave elastography that uses automated region of interest identification through multiple image processing masks, providing accurate liver stiffness measurement and NAFLD diagnosis without requiring tissue sampling, needle insertion, or surgical intervention, thereby maintaining diagnostic accuracy while dramatically improving patient comfort and procedure simplicity
Solution Approach 2:
The system uses automated multi-mask image processing as an intermediary between the ultrasound probe and the final diagnosis, where the combination of liver tissue mask, poor probe contact mask, axial distance mask, and lateral distance mask automatically identifies the region of interest and enables accurate shear-wave elastography measurements without direct tissue contact or invasive procedures
3Productivity
If automated region identification is implemented, then productivity is improved through faster processing, but device complexity increases due to additional processing requirements
Solution Approach 1:
The image processing system is segmented into multiple specialized masks (liver tissue mask, poor probe contact mask, axial distance mask, lateral distance mask), where each mask performs a specific function in identifying and filtering regions, allowing the complex automated identification task to be divided into manageable components that improve processing speed while keeping individual algorithm complexities manageable
Solution Approach 2:
The system merges multiple specialized masks into a unified automated region identification process, where the liver tissue mask, poor probe contact mask, axial distance mask, and lateral distance mask work together to automatically identify the region of interest, achieving fast and accurate productivity improvement through the coordinated operation of integrated processing algorithms
4Area of stationary object
If poor probe contact regions are included in analysis, then measurement coverage is improved, but measurement precision deteriorates due to artifacts
Solution Approach 1:
The system extracts and removes poor probe contact regions from the analysis by using a specialized poor probe contact mask that identifies and filters out artifact-prone areas, allowing the system to maintain comprehensive measurement coverage of viable liver tissue while eliminating regions that would compromise measurement precision through the inclusion of artifacts
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
Enhances the accuracy and precision of liver stiffness measurements by accurately defining the region of interest, reducing errors and improving the diagnostic capabilities of ultrasound imaging for NAFLD.
Implementation Method 1
a probe including at least one transducer configured to transmit ultrasonic waves and receive reflected ultrasonic waves
Implementation Method 2
process reflected ultrasonic shear waves to determine an elasticity of the liver
Data Source
AI summary
By example, a method includes: receiving ultrasound image data of a patient, including a segmented region corresponding to a liver; automatically identifying an area for a region of interest within the segmented region, wherein the region of interest corresponds to a region in the liver for performing shear-wave elastography; and presenting, on a display, the ultrasound image data and the area for the region of interest.