Automated E-mode Image Quality Assessment
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Solution Overview
Problem
Manual deformation techniques in quasi-static elasticity imaging require significant operator skill and can result in inconsistent E-mode image data due to variations in tissue deformation, leading to low-quality images that disrupt animations and reduce measurement accuracy.
Innovation Solution
An automatic method for forming E-mode images using quality values that provide real-time feedback and automatic culling of poor images, involving a tissue compressor and image acquisition system to generate a single quality value for adjusting deformation and improving data quality, ensuring all images are in the same physical grid for composite imaging without losing spatial resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual deformation techniques are used to obtain tissue images in different states of deformation, then the technique is versatile and can be used with standard ultrasonic imaging equipment, but the images are inconsistent and low quality due to variations in tissue deformation and operator skill requirements
Solution Approach 1:
The patent replaces manual mechanical deformation with an automated mechanical compression system that applies controlled compressive forces to the tissue. This mechanical system uses a compression device with adjustable compression plates and controlled displacement to eliminate operator variability while maintaining compatibility with standard ultrasonic imaging equipment.
Solution Approach 2:
The patent implements controlled parameter changes by systematically varying compression magnitude, compression rate, and duration according to predetermined protocols. These standardized parameters ensure consistent tissue deformation across different operators and sessions, improving E-mode image data consistency while working within the capabilities of standard imaging equipment.
2Measurement precision
If multiple E-mode images are combined to reduce image noise or provide measurements along different axes, then the measurement quality improves, but low quality images incorporated into the combination decrease the overall quality
Solution Approach 1:
The patent performs preliminary quality assessment and automated selection of images before combining them. The system evaluates each image's quality metrics and selectively combines only those that meet predetermined quality thresholds, preventing low-quality images from degrading the overall composite image quality while maintaining improved signal-to-noise ratios.
3Loss of information
If a time series animation of E-mode images is provided to give additional information to the physician, then the diagnostic information increases, but low quality images create disruptive breaks in the animation
Solution Approach 1:
The patent performs preliminary quality assessment and automated selection of images before creating the time series animation. The system evaluates each image's quality metrics and selectively includes only those that meet predetermined quality thresholds, preventing low-quality images from creating disruptive breaks in the animation while maintaining comprehensive diagnostic information.
4Measurement precision
If composite E-mode images are obtained by averaging images to reduce noise, then the signal-to-noise ratio improves, but spatial resolution may be lost
Solution Approach 1:
The patent applies local quality by performing averaging only within localized regions or channels where it provides benefit, while preserving high-resolution structural information in other areas. This selective averaging approach improves signal-to-noise ratio in specific measurement regions without compromising overall spatial resolution of the composite image.
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 enables the creation of high-quality composite E-mode images with improved signal-to-noise ratios, providing effective operator feedback and training tools while maintaining spatial resolution, and automatically selecting the best image signals for optimal results.
Implementation Method 1
a tissue compressor adapted to apply a varying deformation to tissue
Implementation Method 2
images of the tissue during different stages of deformation by the tissue compressor
Implementation Method 3
an ultrasonic transducer and may also provide echo signals for the image acquisition system
Implementation Method 4
Strain is deduced from two images by computing a gradient in displacement between the images along any desired direction
Data Source
AI summary
Image data and E-mode images used in ultrasonic elasticity imaging may be automatically evaluated for quality to provide a single value used as operator feedback or for automatic selection of images for averaging or animation.