X-ray CT Volume Data Blending for Boundary Smoothing
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Solution Overview
Problem
Conventional X-ray computed tomography apparatuses face challenges in reconstructing volume data due to regions with no projection data on the boundary, leading to incomplete images and visible boundaries between combined volume data sets, which affects image quality.
Innovation Solution
The apparatus includes an X-ray generating unit, area detector, reconstruction processing unit, extraction unit, calculation unit, determination unit, and combining unit that calculates differences in pixel values, determines the presence of CT value steps, and performs weighted addition of pixel values from overlapping regions to generate a combined image, while adding noise to prevent high apparent contrast.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If multiple volume data sets are combined to display a wider range, then the coverage area is improved, but visible boundaries and image quality degradation occur at the joint portions
Solution Approach 1:
The patent applies local quality by performing weighted addition specifically in the overlap region between volume data sets, rather than uniformly processing the entire combined image. The weighting coefficients vary locally based on the distance from the boundary, with pixels closer to the boundary receiving higher weights from both adjacent volume data sets. This localized processing smooths the transition at joint portions while preserving image quality in non-overlap regions.
Solution Approach 2:
The patent creates a composite image by combining multiple volume data sets with different weighting coefficients in the overlap region. Instead of simply concatenating or selecting one data set, it generates a composite where pixel values are weighted sums of corresponding pixels from multiple source volume data sets, producing a seamless combined image that integrates information from all inputs.
2Loss of information
If approximate interpolation is used to fill regions with no volume data, then the completeness of the image is improved, but image quality and accuracy deteriorate
Solution Approach 1:
The patent merges multiple volume data sets in the overlap region to reconstruct pixels in areas that would otherwise have no data. By combining information from adjacent volume data sets using weighted addition, the method fills gaps and extends the effective field of view without relying on approximate interpolation, thereby maintaining both completeness and quality.
3Productivity
If simple combination of volume data is performed, then the processing speed is improved, but image quality deteriorates due to apparent boundaries at joint portions
Solution Approach 1:
The patent changes the parameter of pixel values by applying weighted addition with distance-dependent weighting coefficients. This parameter transformation smooths the CT values at boundary portions by gradually transitioning between different volume data sets, eliminating apparent boundaries while maintaining processing efficiency through a systematic mathematical approach.
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 improves image quality by smoothing boundaries between volume data sets and enhancing the reliability of reconstructed images, allowing for better diagnosis and internal structure tracing across overlapping regions.
Implementation Method 1
an X-ray generating unit for generating X-rays, and an area detector for detecting the X-rays generated by the X-ray generating unit
Data Source
AI summary
According to one embodiment, an X-ray computed tomography apparatus includes an X-ray generating unit and an area detector. The reconstruction processing unit reconstructs first and second volume data including an overlap region. The extraction unit extracts first and second slice images from the first and the second volume data respectively. The calculation unit calculates the difference value between a sum of pixel values in the first slice images and the sum of pixel values in the second slice images. The determination unit determines whether the difference value falls within a predetermined range. The combining unit combines the first and second volume data and sets a pixel value in the overlap region to a pixel value of the first volume data, a pixel value of the second volume data, or a value derived from pixel values of the first and second volume data.