Iterative CT Reconstruction with Component-Specific Noise Correction
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Solution Overview
Problem
Existing imaging systems using computed tomography struggle to reconstruct high-quality images due to reduced quality caused by noise and beam hardening effects, despite using noise models for iterative updates.
Innovation Solution
An imaging system and method that determine first and second component attenuation values for different elements within a region of interest, considering the noise dependence on these components, and correct for beam hardening using these values to improve image quality during iterative reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If iterative reconstruction with noise model is used, then image reconstruction is performed, but image quality is reduced
Solution Approach 1:
The patent applies local quality by determining component-specific attenuation values (first component attenuation values and second component attenuation values) for different materials in the region of interest. Instead of using a uniform noise model, the system calculates noise values based on the specific composition along each detection path, allowing the noise characteristics to vary locally according to the actual tissue composition. This resolves the contradiction by making the noise model adaptive to local conditions rather than applying a generic approach.
Solution Approach 2:
The patent changes parameters by determining noise values dynamically from component attenuation values rather than using a fixed noise model. The system calculates first and second component attenuation values for different materials (e.g., bone and soft tissue) and uses these to derive noise values that reflect the actual physical conditions. This parameter change allows the reconstruction to account for the fact that noise characteristics depend on the specific materials traversed by the radiation, thereby improving image quality while properly modeling noise.
2Productivity
If polychromatic radiation is used, then imaging is performed, but beam hardening reduces detection value quality
Solution Approach 1:
The patent addresses beam hardening by determining component attenuation values for different materials along each detection path. By identifying the specific composition (first component, second component, etc.) that the radiation traverses, the system can locally correct for beam hardening effects specific to that path. This allows the polychromatic nature of the radiation to be accounted for in a material-specific manner, correcting the detection values based on the actual attenuation characteristics of the traversed materials.
Solution Approach 2:
The patent replaces the physical beam hardening effect with a computational correction model. Instead of physically filtering the polychromatic radiation to prevent beam hardening (which would reduce productivity), the system uses mathematical models to calculate and correct the beam hardening effects based on determined component attenuation values. This substitution allows the use of polychromatic radiation for efficient imaging while computationally removing the harmful beam hardening artifacts.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The approach enhances the quality of iteratively reconstructed images by accurately accounting for noise and beam hardening effects, leading to improved image fidelity and reduced artifacts.
Implementation Method 1
a detection values providing unit for providing acquired detection values of the region of interest, wherein the detection values have been acquired by moving a radiation source emitting radiation and the region of interest relative to each other and by detecting the detection values, which are indicative of the radiation after having traversed the region of interest
Implementation Method 2
The radiation emitted by the radiation source is preferentially polychromatic radiation of which lower energies are attenuated stronger than larger energies by the components within the region of interest. This leads to a so-called beam hardening of the radiation
Implementation Method 3
a reconstruction unit for iteratively reconstructing a final image of the region of interest by performing several iteration steps, in which an intermediate image is updated based on the acquired detection values and based on noise values being indicative of the noise of the detection values
Data Source
AI summary
The noise of a detection value acquired by an imaging system (30) can depend on the contributions of different components within a region of interest to be imaged, which has been traversed by radiation (4) causing the respective acquired detection value. This dependence is considered while iteratively reconstructing an image of the region of interest, wherein first component attenuation values, which correspond to elements of a first component within the region of interest, and second component attenuation values, which correspond to elements of a first component within the region of interest, are determined, wherein noise values are determined from the first component attenuation values and the second component attenuation values and wherein the noise values are used for updating the image. This consideration of the dependence of the noise of an acquired detection value on the different components improves the quality of the iteratively reconstructed image.