CBCT Image Reconstruction Using Iterative Total Variation
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Solution Overview
Problem
Existing cone beam computed tomography (CBCT) systems face challenges in generating high-quality images with reduced radiation dosage, often resulting in poor image quality and complex calculations when scanning at fewer gantry angles.
Innovation Solution
A system and method for image reconstruction that involves obtaining projection data from incomplete gantry angles, using an analytical reconstruction algorithm to generate an initial image, determining missing projection data based on the initial image, and performing an iteration process using a total variation algorithm to improve image quality and speed the reconstruction process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If the CT scanner acquires scan data corresponding to fewer gantry angles to reduce radiation dosage, then the radiation dosage received by the patient is reduced, but the image quality deteriorates
Solution Approach 1:
The patent performs preliminary actions by generating an initial image from the incomplete projection data before final reconstruction. This initial image serves as a starting point that guides the subsequent iterative reconstruction process, allowing the system to work with fewer projection angles while still achieving high-quality final images through the two-stage reconstruction approach
Solution Approach 2:
The patent implements feedback mechanisms in the iterative reconstruction process where the reconstructed image is continuously refined by comparing it with the original projection data. The algorithm adjusts the image reconstruction in each iteration based on the discrepancy between the projected image and actual measured data, enabling high-quality reconstruction from incomplete angular data
2Object-affected harmful factors
If existing methods are used to generate images based on scan data corresponding to fewer gantry angles, then radiation dosage is reduced, but the calculation becomes complicated
Solution Approach 1:
The patent divides the image reconstruction process into two distinct stages: initial image generation from incomplete projection data, and iterative refinement to achieve final high-quality reconstruction. This segmentation allows each stage to use optimized algorithms appropriate for its specific task, reducing overall computational complexity compared to attempting single-step reconstruction from limited angles
Solution Approach 2:
The patent performs preliminary image generation as a separate preparatory step before the main iterative reconstruction. This preliminary action creates a reasonable initial estimate that accelerates convergence in the subsequent iterative process, reducing the number of iterations needed and thereby simplifying the overall calculation
3Object-affected harmful factors
If existing methods are used to generate images based on scan data corresponding to fewer gantry angles, then radiation dosage is reduced, but the reconstruction efficiency becomes low
Solution Approach 1:
The patent performs preliminary image generation as a separate preparatory step before the main iterative reconstruction. This preliminary action creates a reasonable initial estimate that accelerates convergence in the subsequent iterative process, reducing the number of iterations needed and thereby improving reconstruction efficiency
Solution Approach 2:
The patent implements feedback mechanisms in the iterative reconstruction process where the reconstructed image is continuously refined by comparing it with the original projection data. This feedback-driven approach ensures rapid convergence to an accurate solution, maintaining high reconstruction efficiency even when working with incomplete angular data
Data Source
AI summary
A method for image reconstruction may include obtaining projection data D0 generated by an imaging device by scanning an object at first angles, wherein the first angles may be a subset of second angles. The second angles may include at least short-scan angles for a system to conduct image reconstruction. The method may also include generating an image F1 based on the projection data D0. The method may also include determining, based on the image F1, projection data D1 corresponding to third angles that are a subset of the second angles and different from the first angles. The method may also include generating a final image associated with the object by performing an iteration process including one or more iterations using initial data including the image F1, the projection data D0, and the projection data D1.