Cone Beam Local Tomography Artifact Suppression
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Solution Overview
Problem
Cone beam local tomography in three dimensions faces challenges with non-local artifacts that are as strong as the useful singularities, making it difficult to accurately reconstruct images without suppressing important features.
Innovation Solution
A method that differentiates cone beam projection data along the tangent direction of the scan trajectory to suppress artifacts, allowing for the reconstruction of images with reduced non-local artifacts while preserving the strength of useful features, and includes a shift correction for accurate location of moving objects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional cone beam local tomography is used to reconstruct images, then useful singularities are preserved, but non-local artifacts with equal strength are created
Solution Approach 1:
The patent applies differential operators of higher order to the cone beam projection data before backprojection. By changing the mathematical parameter of the reconstruction operator from first-order to second-order or higher derivatives, the artifacts are suppressed by one order in Sobolev spaces while preserving the useful singularities. This parameter change transforms the reconstruction process to achieve both goals simultaneously.
Solution Approach 2:
Instead of directly reconstructing the image using conventional operators, the patent inverts the approach by first applying differentiation operators to enhance the singularities and then performing backprojection. This inverted sequence of operations—differentiation before backprojection rather than after—allows the useful features to be emphasized while the artifact formation is suppressed at the source.
2Object-generated harmful factors
If artifacts are suppressed in the reconstruction, then image quality improves, but useful features may also be suppressed
Solution Approach 1:
The patent employs direction-dependent differentiation operators that act differently on different components of the projection data. By applying derivatives along specific directions (tangent to the scan trajectory) rather than isotropically, the method selectively suppresses artifacts in certain directions while preserving useful singularities in other directions. This local quality approach allows differential treatment of different image components.
Data Source
AI summary
Methods, systems and processes for providing efficient image reconstruction using local cone beam tomography which provide a reduced level of artifacts without suppressing the strength of the useful features; and in a dynamic case provide reconstruction of objects that are undergoing a change during the scan. An embodiment provides a method of reconstructing an image from cone beam data provided by at least one detector. The method includes collecting CB projection data of an object, storing the CB projection data in a memory; and reconstructing the image from the local CB projection data. In the reconstructing step, a combination of derivatives of the CB projection data that will result in suppressing the artifacts are found. The combination of derivatives includes collecting cone beam data that represents a collection of integrals that represent the object.