Radiography Image Scatter Correction via Computational Grid Substitution
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Solution Overview
Problem
Existing radiography image processing methods face challenges in enhancing contrast while avoiding the clinical workflow restrictions imposed by anti-scatter devices, such as anti-scatter grids, which are cumbersome and require precise positioning.
Innovation Solution
A method that estimates a scatter signal in radiography images, calculates a scatter removal signal indicative of removable scattered radiation, and corrects the image based on this signal, effectively mimicking the contrast enhancement of a reference anti-scatter device without physically employing it, thereby circumventing workflow restrictions and preventing artifacts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If anti-scatter devices are employed to counteract contrast reduction, then image contrast is improved, but device complexity and workflow restrictions increase
Solution Approach 1:
The patent replaces the mechanical anti-scatter grid system with a computational image processing system. The method estimates scatter radiation distribution using algorithms and corrects the image digitally, eliminating the need for physical anti-scatter devices and their associated positioning and alignment requirements.
Solution Approach 2:
The patent creates a computational model that replicates the scatter removal function of physical anti-scatter grids. By modeling scatter radiation patterns and applying correction algorithms, the system copies the contrast enhancement effect without requiring the actual physical grid apparatus.
2Reliability
If anti-scatter grids are used to remove scattered radiation, then scatter correction is improved, but ease of operation deteriorates due to positioning requirements
Solution Approach 1:
The patent substitutes the mechanical positioning and alignment system with an automated computational system. The scatter estimation algorithms automatically calculate scatter distribution based on the acquired image data, eliminating manual grid positioning and alignment operations.
Solution Approach 2:
The computational system performs scatter correction autonomously without requiring operator intervention for device positioning. The algorithms self-adjust to the specific imaging conditions and automatically apply appropriate correction factors based on the estimated scatter signal.
3Reliability
If high-pass frequency filtering is used to increase image contrast, then contrast enhancement is improved, but signal-to-noise ratio deteriorates
Solution Approach 1:
The patent converts the harmful scatter signal into useful information for correction. By estimating the scatter signal and using it to generate correction factors, the method transforms the noise problem into a structured correction process that preserves signal-to-noise ratio while enhancing contrast.
Solution Approach 2:
The patent applies targeted parameter changes to specific regions of the image based on estimated scatter distribution. Rather than applying uniform high-pass filtering that degrades overall signal-to-noise ratio, the method selectively adjusts parameters in areas affected by scatter while preserving signal quality in other regions.
Data Source
AI summary
A method and system for processing a radiography image derived from an X-ray radiation passing through an object. The method includes acts of estimating, based on the radiography image, a scatter signal present in said radiography image; calculating, based on the estimated scatter signal, a scatter removal signal indicative of a scattered radiation removable from the X-ray radiation passing through the object by a reference anti-scatter device; and correcting the radiography image based on the scatter removal signal.