Spectral CT Reconstruction via Coupled Iterative Algorithms
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Solution Overview
Problem
Current computed tomography methods, particularly filtered back projection, face challenges with cone beam artifacts, spiral artifacts, and limited-view artifacts, which affect image sharpness and noise levels, and struggle to create more than two spectral datasets with a single x-ray source.
Innovation Solution
A method and system for reconstructing complete spectral images by recording projection measurement data in disjoint angular sectors with different x-ray spectra using a common x-ray source-detector system, employing coupled iterative reconstruction to minimize limited-view artifacts and achieve improved image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If filtered back projection method is used for image reconstruction, then reconstruction speed is improved, but image quality deteriorates due to cone beam artifacts, spiral artifacts, and limited-view artifacts
Solution Approach 1:
The patent divides the projection data into multiple angular sectors and processes each sector separately through iterative reconstruction, then combines the results. This segmentation approach reduces artifacts while maintaining computational efficiency by focusing iterations on specific angular ranges rather than processing all data at once.
Solution Approach 2:
The patent modifies reconstruction parameters by using iterative methods with adjustable convergence criteria and regularization parameters. These parameter changes allow balancing between reconstruction speed and image quality, reducing artifacts while controlling computational load through parameter optimization.
2Manufacturing precision
If iterative reconstruction method is used to reduce artifacts and improve image quality, then image quality is improved, but reconstruction time increases
Solution Approach 1:
By segmenting the projection data into angular sectors and applying iterative reconstruction to each sector separately, the patent reduces the computational burden of full-data iterative processing. This allows achieving artifact reduction with lower computational cost and shorter reconstruction time.
Solution Approach 2:
The patent applies iterative reconstruction partially by limiting iterations to specific angular sectors rather than performing exhaustive iterations on all data. This partial action achieves sufficient artifact reduction without the full computational cost of complete iterative processing.
3Device complexity
If a single x-ray source is used to record projection data, then device complexity is reduced, but the ability to create multiple spectral datasets is limited
Solution Approach 1:
The patent uses dynamic spectral filtering where the x-ray spectrum is varied during the scan by changing filter positions or materials. This dynamic adjustment allows a single x-ray source to generate multiple spectral datasets with different energy characteristics, achieving spectral versatility without adding multiple sources.
Solution Approach 2:
The patent changes spectral parameters by adjusting filter characteristics during data acquisition. By varying filter materials, thicknesses, or positions, a single x-ray source can produce projection data with different spectral shapes, enabling creation of multiple spectral datasets from one source through parameter modulation.
Data Source
AI summary
A method is for imaging of an examination region of an object to be examined with a computed tomography system. In an embodiment, the method includes recording of first and second projection measurement data with a common x-ray source-detector system, the first projection measurement data being recorded with a first x-ray spectrum in a first angular sector and the second projection measurement data being recorded with a second x-ray spectrum in a second angular sector; Creation of first and second start image data from the first and second projection measurement data via a first reconstruction method; and coupled iterative reconstruction of first result image data on the basis of the first start image data and of second result image data on the basis of the second start image data, the first result image data and the second result image data each featuring a complete image of the examination region.