Radiation Component Imaging With Body-Thickness Constraints
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Solution Overview
Problem
Existing energy subtraction processing methods struggle to accurately separate multiple components in a subject due to variations in the composition of soft tissues, such as fat and muscle, which are mixed and vary among individuals, limiting the separation of components like bone and soft parts using radiation images obtained with different energy distributions.
Innovation Solution
A radiation image processing device and method that utilizes n radiation images with different energy distributions to derive body thickness and component thicknesses, enabling the enhancement and separation of n components by using a processor to analyze images acquired with n - 1 types of radiation, specifically separating fat, muscle, and bone components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If energy subtraction processing is performed using two radiation images with different energy distributions, then two components (bone part and soft part) can be separated, but n components cannot be separated when n ≥ 3
Solution Approach 1:
The patent segments the soft part into multiple components (fat and muscle) by introducing a body thickness map as an additional parameter. This allows the system to solve for multiple unknowns (fat thickness, muscle thickness, bone thickness) by using the body thickness constraint, thereby enabling separation of n components with n-1 radiation images.
2Manufacturing 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 is not possible
Solution Approach 1:
The patent performs preliminary action by acquiring a body thickness map before component separation. This body thickness information is used as a constraint to determine the attenuation coefficients and separation ratios of fat and muscle, thereby enabling accurate component separation without requiring complex iterative optimization during the main processing stage.
3Manufacturing precision
If n radiation images are used to separate n components, then accurate separation is possible, but the number of required radiation images increases
Solution Approach 1:
The patent changes the parameter space by introducing body thickness as an additional known parameter. This allows the system to determine n component thicknesses using only n-1 radiation images, because the body thickness provides an additional constraint equation that compensates for the reduced number of measurement equations.
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 n components in a subject by enhancing and displaying fat, muscle, and bone images using n radiation images with different energy distributions, improving the precision of component separation in radiation imaging.
Implementation Method 1
the attenuation coefficient of the soft part is required... using the facts that an attenuation amount of 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 first to nth components each consisting of a single composition, with n - 1 types of radiation having different energy distributions; acquire a body thickness of the subject; derive thicknesses of the first to nth components by using the body thickness 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.