Multi-Energy Radiation Image Processing for Component Separation
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Solution Overview
Problem
Existing energy subtraction processing methods using two radiation images with different energy distributions fail to accurately separate multiple components in a subject due to variations in the composition of soft tissues, such as fat and muscle, leading to incomplete separation of components like bone and soft parts.
Innovation Solution
A radiation image processing device and method that utilizes n radiation images with different energy distributions to derive characteristics and thicknesses of components, enabling accurate separation of n components by deriving attenuation coefficients and body thicknesses, enhancing component images individually.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If energy subtraction processing is performed using two radiation images with different energy distributions, then bone parts and soft parts can be separated, but multiple components (n components) cannot be accurately separated because only n component images can be obtained from n radiation images
Solution Approach 1:
The patent changes the parameter of radiation energy distribution by using n-1 types of radiation with different energy distributions. By deriving attenuation coefficients at multiple energy levels and using body thickness information, the system can separate n components (including soft parts, bone parts, and artificial objects) from only n-1 radiation images, achieving accurate multi-component separation without requiring n images for each component
Solution Approach 2:
The patent introduces body thickness as an additional dimension of information to resolve the component separation problem. By combining attenuation coefficient data from multiple energy levels with body thickness measurements, the system creates a multi-dimensional parameter space that enables separation of n components using only n-1 radiation images, effectively adding a dimensional constraint to the inverse problem
2Measurement precision
If the attenuation coefficient of the soft part is not obtained in accordance with the ratio between fat and muscle, then accurate separation of multiple components cannot be achieved
Solution Approach 1:
The patent segments the soft part into multiple components (fat and muscle) and derives their respective attenuation coefficients separately. By dividing the soft part region and calculating attenuation coefficients for each component based on their different energy-dependent attenuation characteristics, the system can accurately determine the composition ratio and achieve precise separation of soft tissue components
Solution Approach 2:
The patent uses feedback by iteratively deriving attenuation coefficients at multiple energy levels and comparing the derived body thickness with measured body thickness. This feedback loop allows the system to adjust and refine the attenuation coefficients of soft tissue components until the calculated and measured values converge, ensuring accurate determination of fat and muscle ratios
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
Accurately separates multiple components in a subject by using n radiation images, allowing for precise differentiation of components like soft parts and bone parts, as well as artificial objects, through enhanced image processing.
Implementation Method 1
the attenuation amount of the transmitted radiation differs in accordance with the substance constituting the subject
Data Source
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AI summary
A processor is configured to: acquire first to (n - 1)th (n ≥ 3) radiation images acquired by imaging a subject, which includes a first component consisting of a plurality of compositions and second to nth components each consisting of a single composition, with n - 1 types of radiation having different energy distributions; derive a characteristic of the first component in at least a region of the subject in the first to (n - 1)th radiation images; acquire a body thickness of the subject; derive thicknesses of the first to nth components by using the body thickness, the characteristic of the first component, and the first to (n - 1)th radiation images; and derive first to nth component images in which the first to nth components are enhanced, respectively, based on the thicknesses of the first to nth components.