X-ray CT Projection Data Correction Using Segmented Air Data
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Solution Overview
Problem
Existing X-ray CT apparatuses face challenges in accurately removing sensitivity variations from measurement data, leading to ring-like artifacts in images, and insufficient noise reduction due to the influence of bowtie filters, which complicates maintenance and increases costs when trying to exclude the filter.
Innovation Solution
An X-ray CT apparatus and data processing device that extracts sensitivity variation data from air data, removes sensitivity variations and noise from measurement data, and performs a correction process using blank data to generate projection data, thereby isolating the influence of the bowtie filter and improving image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If noise reduction process is applied to measurement data, then noise is reduced, but sensitivity variations are also reduced causing ring-like artifacts
Solution Approach 1:
The patent segments the air data into two distinct components: sensitivity variation data and blank data. This segmentation allows the sensitivity variation component to be extracted and handled separately from the noise component, enabling noise reduction to be applied only to the blank data while preserving the sensitivity variation information for accurate correction of measurement data.
Solution Approach 2:
The patent extracts the sensitivity variation component from the air data by dividing the air data by the sensitivity variation data. This extraction separates the sensitivity variation factor from other factors (including noise and bowtie filter effects), allowing independent processing of each component to resolve the contradiction between noise reduction and artifact prevention.
2Reliability
If air correction is performed using air data after noise reduction, then ring-like artifacts are avoided, but bowtie filter influence remains causing insufficient noise reduction
Solution Approach 1:
The patent segments the correction process into two distinct stages: first applying noise reduction to the blank data (which contains only noise and bowtie filter effects), then applying air correction using the processed blank data. This segmentation allows noise reduction to be effectively applied without compromising the correction accuracy, as the sensitivity variation component has been separately handled.
3Measurement precision
If bowtie filter is excluded to scan sensitivity variations, then sensitivity variations can be separately scanned, but apparatus complexity and maintenance cost increase
Solution Approach 1:
The patent creates a computational model (copy) of the sensitivity variation by processing air data through mathematical operations (division and extraction) rather than requiring a physical modification of the apparatus. This virtual copying approach achieves the same goal as physical exclusion of the bowtie filter without adding mechanical complexity or maintenance burden.
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 allows for the generation of projection data with satisfactory image quality by accurately removing sensitivity variations, reducing ring-like artifacts, and enabling effective noise reduction without underestimating noise, thus improving the overall image quality and simplifying maintenance.
Implementation Method 1
The X-ray CT apparatus emits X-ray using multiple angles around an object, and causes an X-ray detector to acquire the X-ray attenuated by the object
Implementation Method 2
the X-ray generated in an X-ray tube is transmitted through a bowtie filter, and thereafter, the X-ray beam is emitted to the object
Data Source
AI summary
An X-ray CT apparatus includes an extraction unit that acquires air data measured using the X-ray CT apparatus and the measurement data obtained by scanning the object, that extracts sensitivity variation data which is a sensitivity variation component of a detection element from the air data, and that extracts blank data from which the sensitivity variation component is removed, and a projection data generation unit that removes the sensitivity variation component and noise which are included in the measurement data, based on the sensitivity variation data, and that uses the blank data so as to perform a correction process of the measurement data from which the sensitivity variation component and the noise are removed.