Method for Reconstructing a Three-Dimensional Image Dataset from Two-Dimensional Projection Images, X-Ray Device and Computer Program

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This patent describes a method and system for reconstructing three-dimensional images from two-dimensional X-ray projection images. The invention uses a specific filtering sequence involving Laplace, spike, and residual filters, combined with a mathematical correction step, to improve the accuracy and quality of the reconstructed 3D image dataset. It also covers associated X-ray device configurations and computer software implementing the method.

Use CasesContent extracted from patent full text and abstract with AI.

• Medical imaging (such as CT scans) for more accurate diagnostics
• Non-destructive testing in industrial inspection
• Archaeological or paleontological imaging to reconstruct objects from X-ray scans
• Security scanning in airports or border controls for precise 3D imaging of luggage or cargo
• Integration with advanced imaging software and X-ray machinery for research purposes

BenefitsContent extracted from patent full text and abstract with AI.

• Improves the quality and fidelity of 3D images reconstructed from 2D X-ray data
• Reduces artifacts and distortions around image boundaries
• Enables more accurate imaging without requiring more complex or higher-dose X-ray scans
• Can be implemented in software, making it adaptable to existing imaging systems
• Supports more reliable diagnosis or inspection in both medical and industrial fields

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Patent Abstract

A method for reconstructing a three-dimensional image dataset from two-dimensional projection images includes recording the projection images using a collimator downstream of an X-ray source. A local Laplace filter is initially applied to the projection data of the projection images during the reconstruction using filtered back-projection. After this, high-frequency spikes arising in the Laplace-filtered projection data at boundaries to the image region are removed by a spike filter, and a global residual filter is applied. A fit parameter describing a fit function approximating the projection data characteristic in the uncorrected projection images inside the image region is determined based on at least marginal values of the projection data present at the boundaries. Next, following on from the use of the residual filter, an additive correction of the residual-filtered projection data in the image region is performed with the fit function scaled by a scaling factor.