Panoramic Ultrasound Elasticity Imaging Dynamic Range Normalization
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Solution Overview
Problem
Existing ultrasound imaging technologies face challenges in generating panoramic elasticity images due to varying dynamic ranges of elasticity data from different fields of view, leading to frame-to-frame artifacts and incorrect motion differentiation between elasticity and extended field of view motion.
Innovation Solution
The method involves acquiring elasticity data from multiple fields of view with different compression levels, normalizing the data to update the dynamic range, and decomposing displacement vectors to combine frames effectively, using radio frequency data for alignment and noise suppression techniques to generate a panoramic elasticity image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If elasticity data from multiple fields of view with different compression levels is combined, then the extended field of view is achieved, but frame-to-frame artifacts occur due to varying dynamic ranges
Solution Approach 1:
The patent applies parameter changes by normalizing the dynamic range of elasticity data from different fields of view. Specifically, the system adjusts the dynamic range parameters of elasticity data acquired at different compression levels to a common reference frame, allowing artifacts to be identified and corrected through parameter transformation rather than direct data combination
Solution Approach 2:
The patent introduces an intermediary reference frame that serves as a common baseline for comparing and combining elasticity data from multiple fields of view. This reference frame acts as a mediator that standardizes the dynamic ranges before artifact detection and correction, enabling reliable panoramic elasticity imaging
2Measurement precision
If displacement vectors are used to assemble frames, then relative motion between frames is detected, but incorrect motion differentiation occurs between elasticity and extended field of view motion
Solution Approach 1:
The patent segments the displacement vector into two distinct components: one representing elasticity-related tissue deformation and another representing extended field of view motion. By separating these motion components, the system can accurately differentiate between true elasticity signals and artifacts caused by transducer movement or patient motion
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors displacement vectors and adjusts the assembly process based on detected motion patterns. When incorrect motion differentiation is detected, the system uses feedback loops to correct the alignment and reassemble frames with proper motion compensation
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 minimizes frame-to-frame artifacts and accurately represents tissue elasticity across extended fields of view, providing a clear and artifact-free panoramic image for clinical use.
Implementation Method 1
elasticity data from two or more different fields of view is acquired using tissue compression
Implementation Method 2
First elasticity data is acquired with ultrasound for a first region
Data Source
AI summary
Using compression, tissue elasticity data from two or more different fields of view are acquired. Since different amounts of compression may be used for the different fields of view, the dynamic range of the elasticity data is updated. A panoramic elasticity image is generated from the updated elasticity data of multiple fields of view. A panoramic elasticity image represents the combined fields of view for the elasticity data.