Multi-Material CT Image Correction via Basis Decomposition
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Solution Overview
Problem
Current non-invasive imaging technologies, such as CT systems, face challenges in producing accurate images due to artifacts like beam hardening, heel-effect related spectral variations, and bone-induced spectral artifacts, which are not effectively addressed by existing empirically based correction techniques.
Innovation Solution
A multi-material correction approach that characterizes and decomposes image volumes into two basis materials, such as water and iodine, to generate re-mapped image volumes and perform forward projections, resulting in linearized multi-material corrected projections that minimize beam hardening artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If empirically based correction techniques are used, then the correction process is simple to implement, but the accuracy of artifact correction is insufficient
Solution Approach 1:
The patent transforms the correction approach by changing from empirical parameters to physics-based parameters. The system uses known physical properties of basis materials (attenuation coefficients, spectral characteristics) to model and correct artifacts, replacing inaccurate empirical corrections with theoretically grounded parameter transformations that improve accuracy while maintaining computational feasibility
Solution Approach 2:
The patent replaces empirical correction methods with a physics-based computational model. Instead of using heuristic algorithms tuned to specific cases, the system substitutes a theoretical framework based on X-ray physics principles, material decomposition, and spectral modeling that provides generalizable and accurate artifact correction across different imaging scenarios
2Measurement precision
If multi-material decomposition is performed, then material-based correction accuracy is improved, but processing time increases
Solution Approach 1:
The patent segments the complex multi-material correction problem into manageable components: first decomposing the image into basis material components, then performing correction on each component separately, and finally recombining results. This segmentation allows the system to handle material complexity systematically while optimizing processing efficiency through targeted corrections rather than full-reconstruction approaches
Solution Approach 2:
The patent performs material decomposition and basis material separation as preliminary steps before the actual artifact correction process. By pre-characterizing the material composition and spectral properties, the system prepares corrected projection data in advance, which accelerates the subsequent correction steps and reduces overall processing time compared to performing all operations simultaneously
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 provides more accurate and consistent CT values for bone, soft tissue, and contrast agents, improving image quality, differentiation between cysts and metastases, and accurate contrast measurement, while being independent of patient size and region-of-interest location.
Implementation Method 1
such as the differential transmission of X-rays through the target volume
Implementation Method 2
beam hardening for non-water materials
Implementation Method 3
the reflection of acoustic waves
Implementation Method 4
In digital X-ray systems a photodetector produces signals representative of the amount or intensity of radiation impacting discrete pixel regions
Data Source
AI summary
A method is provided. The method includes acquiring projection data of an object from a plurality of pixels, reconstructing the acquired projection data from the plurality of pixels into a reconstructed image, performing material characterization and decomposition of an image volume of the reconstructed image to reduce a number of materials analyzed in the image volume to two basis materials. The method also includes generating a re-mapped image volume for at least one basis material of the two basis materials, and performing forward projection on at least the re-mapped image volume for the at least one basis material to produce a material-based projection. The method further includes generating multi-material corrected projections based on the material-based projection and a total projection attenuated by the object, which represents both of the two basis materials, wherein the multi-material corrected projections include linearized projections.