CT Image Reconstruction Using Finite Detector and Focal Spot Models
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Solution Overview
Problem
Conventional model-based iterative CT reconstruction techniques are inaccurate due to the neglect of finite detector element and focal spot sizes in CT scanners.
Innovation Solution
A method and system that acquire CT data and reconstruct images by using forward and back projection models associated with the sizes of detector units and the focal spot, involving the creation of voxel representations and ranking intersection points to determine these models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional model-based iterative CT reconstruction techniques are used, then the reconstruction process is simple and fast, but the image reconstruction accuracy is poor due to neglecting finite detector element and focal spot sizes
Solution Approach 1:
The patent applies parameter changes by incorporating the finite sizes of detector elements and focal spots as explicit parameters in the forward projection and back projection models. Instead of using idealized point detectors and line sources, the model uses actual physical dimensions of these components, thereby improving measurement precision without fundamentally changing the reconstruction algorithm structure
Solution Approach 2:
The patent transitions from a zero-dimensional point detector model to a two-dimensional detector element model by considering the spatial extent of detector elements and focal spots. This dimensional expansion allows the model to account for geometric effects that were previously neglected, improving image reconstruction accuracy while adding manageable complexity through systematic modeling
2Measurement precision
If the finite sizes of detector elements and focal spots are taken into account, then the image reconstruction accuracy is improved, but the computational complexity and processing time increase
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing the forward projection and back projection models that incorporate detector element and focal spot sizes. These pre-computed models are then reused during the iterative reconstruction process, avoiding redundant calculations and reducing processing time while maintaining improved accuracy
3Ease of manufacture
If idealized point detectors and line sources are used in the reconstruction model, then the model is simple and computationally efficient, but the model does not reflect the actual physical characteristics of the CT scanner
Solution Approach 1:
The patent applies local quality by making the reconstruction model locally accurate to the specific CT scanner being used. Instead of using a generic idealized model, the forward projection and back projection models are tailored to incorporate the actual detector element dimensions and focal spot characteristics of the specific scanner, thereby improving model reliability and accuracy for that particular system
Data Source
AI summary
The present disclosure directs to a system and method for CT imaging. The method may include acquiring computed tomography (CT) data, wherein the CT data is generated by scanning a subject using a CT scanner, the CT scanner including a focal spot and a detector, and the detector including a plurality of detector units. The method may also include obtaining a forward projection model and a back projection model, wherein the forward projection model and the back projection model are associated with sizes of the detector units and a size of the focal spot of the CT scanner. The method may further include reconstructing a CT image of the subject iteratively based on the CT data, the forward projection model, and the back projection model.