CT Image Reconstruction Using Virtual Projection Data Fusion
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Solution Overview
Problem
Modern imaging systems, such as CT imaging systems, often have a field of view smaller than the bore size, leading to artifacts in image reconstruction when objects extend beyond the field of view, particularly for high attenuating objects like bone or metal.
Innovation Solution
A system that includes a projection data providing unit, an estimated image data generation unit, a virtual projection data estimation unit, and a data fusion unit to generate fused projection data, allowing for the reconstruction of a complete image by estimating and fusing data from both within and outside the imaging field of view using a virtual imaging unit with a larger field of view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the imaging unit uses a limited detector extent in angular direction, then the device complexity is reduced, but the field of view becomes smaller than the bore size, causing truncation artifacts in image reconstruction
Solution Approach 1:
The system performs preliminary actions by estimating image data for regions outside the imaging FOV before final image reconstruction. The estimated image data generation unit creates preliminary estimates of object regions that extend beyond the detector's angular coverage, which are then used to generate virtual projection data to complete the projection dataset and eliminate truncation artifacts.
Solution Approach 2:
The invention introduces an intermediary virtual imaging unit with a virtual detector that has extended angular coverage. This virtual detector acts as a mediator between the limited physical detector and the complete object, enabling the system to acquire projection data for regions outside the physical FOV by forward-projecting the estimated image data through the virtual detector geometry.
2Manufacturing precision
If the field of view is extended to cover the entire object, then the image reconstruction quality is improved, but the device complexity and cost increase due to larger detector requirements
Solution Approach 1:
The system creates a copy or virtual representation of the imaging unit with extended capabilities. The virtual imaging unit replicates the imaging geometry but with a larger virtual FOV, allowing the physical system to achieve complete object coverage through computational means rather than requiring a physically larger detector.
Solution Approach 2:
The invention changes the parameter of FOV from a fixed physical constraint to a flexible computational parameter. By adjusting the virtual FOV parameters and using iterative estimation algorithms, the system can adaptively extend the effective FOV to match the actual object size without changing the physical detector dimensions.
3Device complexity
If high attenuating objects like bone or metal are located outside the field of view, then the imaging system can maintain a compact design, but the artifacts in the reconstructed image are particularly emphasized
Solution Approach 1:
The system converts the harmful effect of truncated projection data into a benefit by using the truncated data to generate estimated image data, which is then forward-projected to create virtual projection data. This process transforms the incomplete information into a complete projection dataset that eliminates artifacts while maintaining the compact imaging system design.
Data Source
AI summary
The invention relates to a system for reconstructing an image of an object. The system (100) comprises means (110) providing projection data acquired by an imaging unit, like a CT system, with an FOV, means (120) generating estimated image data indicative of a part of an object (20) located outside the FOV (210), means (130) estimating virtual projection data based on virtual settings of a virtual imaging unit comprising a virtual FOV, means (140) generating fused projection data by fusing the provided projection data with the virtual projection data, and means (150) reconstructing a final image. This allows basing the reconstruction on a complete set of projection information for the object and thus providing an image with a high image quality.