X-ray Image Brightness Adaptation via Boundary Correction
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Solution Overview
Problem
Existing X-ray image processing methods using ROI filters face challenges in achieving uniform brightness across different image regions, leading to inadequate image quality due to averaging techniques that fail to account for anatomical variations and changing filter settings during medical interventions.
Innovation Solution
A method for adapting X-ray image brightness by determining correction values along evaluation lines perpendicular to boundaries between filter regions, using filter and recording geometry parameters to scale image values and apply correction factors, thereby improving image quality by accounting for spatial differences in attenuation and anatomical variations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If averaging techniques are used to adapt brightness across image regions, then computational simplicity is maintained, but image quality deteriorates due to failure to account for anatomical variations and spatial differences in attenuation
Solution Approach 1:
The patent applies local quality by determining correction values specifically for boundary regions between filter regions rather than uniformly across the entire image. Evaluation lines are positioned perpendicular to boundaries, and correction factors are calculated based on local image value profiles in these boundary areas. This allows the brightness adaptation to account for local anatomical variations and spatial differences in attenuation, improving image quality without requiring complex global processing of the entire image.
2Object-affected harmful factors
If ROI filter is used to reduce X-ray dose, then radiation exposure is reduced, but brightness uniformity deteriorates across different image regions
Solution Approach 1:
The patent introduces an intermediary brightness adaptation process that operates on the X-ray images after they are captured with the ROI filter. Correction values are determined based on evaluation lines along boundaries between filter regions, and correction factors are calculated to compensate for the brightness differences caused by the filter. This intermediary processing step restores brightness uniformity across image regions while preserving the radiation dose reduction benefits of the ROI filter.
3Adaptability or versatility
If filter regions are changed during intervention, then adaptability to different target regions is improved, but image processing complexity increases due to changing filter settings
Solution Approach 1:
The patent applies preliminary action by pre-defining evaluation lines perpendicular to boundaries between filter regions and establishing a systematic method for determining correction values along these lines. The control device is configured to automatically determine correction values and calculate correction factors based on image value profiles along the evaluation lines. This preliminary setup and automated process reduces the complexity of processing changing filter settings during interventions, as the same systematic approach can be applied regardless of which filter region is currently active.
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 provides targeted brightness adaptation, resulting in high-quality X-ray images with improved uniformity and reduced computational effort, enhancing the interpretability of X-ray images during medical interventions.
Implementation Method 1
a filter is connected downstream of the X-ray source of the X-ray device attenuating the X-ray radiation at least in less relevant portions of the region recorded
Data Source
AI summary
A method for adapting the brightness of an X-ray image is provided. The X-ray image is recorded using a filter attenuating X-ray radiation used for recording the X-ray image differently in at least two spatial filter regions. The method includes determining image regions mapping the filter regions from filter parameters and recording geometry parameters describing the filter regions from at least one evaluation line running perpendicular to a boundary between image regions. The method also includes determining, for each evaluation line, a correction value describing a difference in brightness between the image regions from an image value profile along the evaluation line in an evaluation area containing the boundary, determining at least one correction factor from the at least one correction value, and adapting the brightness between the at least two image regions by scaling the image values with the correction factor.