Inverse Geometry CT Source Fluctuation Correction
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Solution Overview
Problem
Conventional CT scanners face challenges in correcting x-ray source intensity fluctuations in inverse geometry CT systems due to the inability of reference channels to illuminate all sources, leading to image artifacts.
Innovation Solution
A method is introduced where projection data from one source with known intensity is used to correct for fluctuations in another source by leveraging overlap regions in projection space, allowing for sequential normalization of data from all sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If reference channels are used to correct source intensity fluctuations, then source normalization is improved, but this method cannot illuminate all sources in inverse geometry CT systems leading to image artifacts
Solution Approach 1:
The patent uses projection data from one source as an intermediary to correct fluctuations in another source. Specifically, projection data from a first source with known intensity serves as a mediator to normalize projection data from a second source with unknown fluctuations, enabling correction without direct reference channel illumination of the second source.
Solution Approach 2:
The patent creates a virtual reference by copying the normalization approach: instead of having each source directly illuminated by a reference channel, the system copies the correction mechanism by using overlap regions where projection data from one source can serve as a reference for another source's fluctuations.
2Manufacturing precision
If multiple sources are used to improve imaging coverage, then image quality is improved, but source intensity fluctuations from unknown sources create image artifacts
Solution Approach 1:
The patent implements a feedback mechanism where projection data from sources with known intensity provides continuous reference information that feeds back into the correction process. The overlap regions enable the system to continuously monitor and correct for fluctuations in sources with unknown intensity, creating a self-correcting system that maintains image quality despite multiple variable sources.
3Measurement precision
If projection data overlap regions are used for correction, then source fluctuation correction is improved, but data processing complexity increases
Solution Approach 1:
The patent segments the correction process into distinct steps: identifying overlap regions between different sources, selecting reference data from sources with known intensity, and applying correction factors to sources with unknown fluctuations. This segmentation makes the complex multi-source correction problem manageable by breaking it into discrete, processable units.
Data Source
AI summary
A method for imaging an object in a computed tomography (CT) system with a plurality of sources comprising a first source and a second source, wherein the plurality of sources together with a detector array are mounted on a rotatable gantry, and wherein an intensity of the second source has unknown fluctuations is provided. Projection data is collected using the first source in a first gantry position. Projection data is collected using the second source in a second gantry position, wherein projection data from the first source in the first gantry position substantially overlaps projection data from the second source in the second gantry position. Data from the first source at the first gantry position is used to correct for source fluctuations of the second source at the second gantry position.