X-Ray Imaging Scatter Correction Through Iterative Sample Modeling
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Solution Overview
Problem
X-ray imaging systems face challenges with scatter correction, as anti-scatter grids increase complexity and patient dose, and multi-absorption plates require additional hardware, while existing scatter correction methods are inefficient and introduce image artifacts.
Innovation Solution
A method for scatter correction that iteratively refines a model of the sample using simulated X-ray image data, eliminating the need for anti-scatter grids or multi-absorption plates by computing direct and scatter contributions, and adjusting scatter kernels based on material composition and thickness, achieving convergence through iterative refinement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an anti-scatter grid is placed between the x-ray detector and the subject, then scatter radiation is absorbed and image quality is improved, but the patient dose must be increased and the system complexity increases
Solution Approach 1:
The patent creates a computational model that replicates the scattering behavior of the imaged object. Instead of using a physical anti-scatter grid, the system simulates how x-rays scatter through the object's materials and uses this model to subtract scattered radiation contributions from the measured image, thereby reducing patient dose while maintaining image quality
Solution Approach 2:
The patent replaces the mechanical anti-scatter grid with a computational approach. The system uses iterative optimization to adjust material properties in a simulated object until the simulated scattered radiation matches the measured scattered radiation, then uses this model to correct the image without requiring physical scatter-absorbing hardware
2Measurement precision
If an anti-scatter grid is placed between the x-ray detector and the subject, then scatter radiation is absorbed and image quality is improved, but the device complexity increases
Solution Approach 1:
The patent creates a computational model that replicates the scattering behavior of the imaged object. Instead of using a physical anti-scatter grid, the system simulates how x-rays scatter through the object's materials and uses this model to subtract scattered radiation contributions from the measured image, thereby reducing patient dose while maintaining image quality
Solution Approach 2:
The patent replaces the mechanical anti-scatter grid with a computational approach. The system uses iterative optimization to adjust material properties in a simulated object until the simulated scattered radiation matches the measured scattered radiation, then uses this model to correct the image without requiring physical scatter-absorbing hardware
3Measurement precision
If a multi-absorption plate is placed in the x-ray beam path, then material properties can be identified through variable perturbation, but additional hardware is required
Solution Approach 1:
The patent creates a computational model that replicates the scattering behavior of the imaged object. Instead of using a physical anti-scatter grid, the system simulates how x-rays scatter through the object's materials and uses this model to subtract scattered radiation contributions from the measured image, thereby reducing patient dose while maintaining image quality
Solution Approach 2:
The patent replaces the mechanical anti-scatter grid with a computational approach. The system uses iterative optimization to adjust material properties in a simulated object until the simulated scattered radiation matches the measured scattered radiation, then uses this model to correct the image without requiring physical scatter-absorbing hardware
4Measurement precision
If existing scatter correction methods are used, then scatter correction is achieved, but image artifacts are introduced and correction efficiency is low
Solution Approach 1:
The patent employs iterative optimization where the simulated scattered radiation is continuously compared with the measured scattered radiation, and the material properties in the computational model are adjusted based on this feedback. This iterative process continues until convergence, producing an accurate scatter correction without introducing artifacts
Solution Approach 2:
The patent creates a computational model that replicates the scattering behavior of the imaged object. Instead of using a physical anti-scatter grid, the system simulates how x-rays scatter through the object's materials and uses this model to subtract scattered radiation contributions from the measured image, thereby reducing patient dose while maintaining image quality
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
This approach improves image quality by reducing patient dose and eliminating artifacts, while providing accurate scatter correction without additional hardware, enhancing the precision of material composition inference.
Implementation Method 1
an x-ray source (emitter) 102 for emitting a beam of x-ray photons
Implementation Method 2
some x-ray photons are scattered by the material
Implementation Method 3
a detector 106 for acquiring an x-ray image of the sample
Data Source
AI summary
A method of performing scatter correction on an X-ray image is disclosed. The method comprises obtaining an input image for processing based on a source X-ray image of a sample acquired using an X-ray detector, and determining a model of the sample based on the input image. The model is then evaluated by computing, based on the model, simulated X-ray image data and evaluating the simulated image data against the input image to determine whether a convergence criterion is fulfilled. An updated model of the sample is generated if the convergence criterion is not fulfilled. The model evaluating step is repeated based on one or more successive updated models until the convergence criterion is fulfilled in a final iteration, and scatter correction is then performed on the source X-ray image using simulated image data computed during the final iteration.