Image Reconstruction for Non-Uniform Objects
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Solution Overview
Problem
Current image reconstruction methods for non-uniform measurement objects face challenges in eliminating image deterioration due to refraction and multiple-reflections, and require impractical calculation times to achieve convergence, making them unsuitable for real-time medical applications.
Innovation Solution
A method and device that calculate physical property values within the measurement object using an evaluation quantity derived from physical equations without approximation, employing a transmit-receive sequence that focuses on signals contributing to image reconstruction, and utilizing numerical calculations to determine the distribution of physical property values through a physical property value calculation step and display value conversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If iterative waveform correction methods are used to account for non-uniform physical property values, then measurement precision is improved, but processing time becomes excessively long and real-time performance cannot be achieved
Solution Approach 1:
The patent performs preliminary classification of measurement points into uniform and non-uniform regions before detailed reconstruction. By pre-identifying which regions require complex iterative processing and which can use simplified methods, the system avoids unnecessary computational overhead while maintaining accuracy where needed. This preliminary action enables the system to achieve real-time performance by reducing overall processing time.
Solution Approach 2:
The patent applies different reconstruction strategies to different spatial regions based on their physical property uniformity. Uniform regions use efficient simplified algorithms, while only non-uniform regions undergo iterative waveform correction. This local differentiation maintains measurement precision in critical non-uniform areas while minimizing processing time across the entire measurement object.
2Productivity
If simplified approximate equations are used for fast processing, then processing time is reduced, but image deterioration occurs due to refraction and multiple-reflections in non-uniform regions
Solution Approach 1:
The patent implements spatially-varying processing quality by classifying measurement points into uniform and non-uniform regions. Simplified approximate equations are applied to uniform regions where they provide sufficient accuracy with fast processing, while iterative waveform correction methods are applied to non-uniform regions where image quality would otherwise deteriorate due to refraction and multiple-reflections. This local quality differentiation resolves the contradiction between speed and accuracy.
Solution Approach 2:
The measurement object is segmented into distinct regions based on physical property uniformity. This segmentation allows the system to apply appropriate processing methods to each segment - fast approximate methods for uniform segments and accurate iterative methods for non-uniform segments - thereby achieving both overall fast processing and localized high image quality.
3Device complexity
If uniform physical property value assumption is made throughout the measurement object, then calculation complexity is reduced and processing is faster, but measurement precision deteriorates in non-uniform regions
Solution Approach 1:
Instead of assuming uniform physical properties throughout the entire measurement object, the patent performs local classification to identify non-uniform regions. The uniform assumption is maintained only in regions where it is valid, while iterative waveform correction is applied specifically to non-uniform regions. This local quality approach reduces calculation complexity compared to applying iterative methods everywhere, while maintaining measurement precision in non-uniform areas.
Solution Approach 2:
The measurement object is segmented into uniform and non-uniform regions based on physical property analysis. This segmentation allows the system to use simple uniform assumptions in appropriate regions (reducing calculation complexity) while applying complex iterative correction only where necessary (maintaining measurement precision). The segmentation strategy optimizes the balance between computational simplicity and accuracy.
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 image reconstruction without image deterioration and achieves a feasible processing time by reducing the calculation scale and signal acquisition time, making it suitable for real-time medical applications.
Implementation Method 1
transmits a measurement signal (for example, ultrasonic waves) to the interior of the measurement object
Implementation Method 2
image deterioration due to phenomena such as refraction and multiple-reflections caused by the non-uniformity
Data Source
AI summary
An objective is to enable calculation of a distribution of a physical property such as a density inside a measurement object, even when the distribution of the physical property value is non-uniform, within a feasible period of time without causing image deterioration due to phenomena such as refraction and multiple-reflections caused by the non-uniformity. To this end, the physical property value that makes an evaluation quantity be an extremum is outputted, where the evaluation quantity is a liner sum or a product of exponential function of: an equation residual quantity that is a residual being a difference between an operator term and an external force term of an equation of motion; a non-uniformity detection equation residual quantity that is a residual of an equation of detecting the non-uniformity of the physical property value from a matching degree of solutions of the equation of motion under two types of boundary conditions; and a conditional equation residual quantity that is a residual of a constraint condition.