Fluoroscopy Intensity Adaptation via Vascular Mask Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In interventional radiology and oncology, achieving optimal contrast in fluoroscopy images is challenging due to varying vascular mask and component intensities, requiring manual adjustments that can be limiting and result in suboptimal image quality.
Innovation Solution
A method for automatically optimizing the contrast between vascular tree and medical component images in fluoroscopy by segmenting and analyzing intensity ratios, using a computing unit to generate an overlay image with a preset contrast ratio, eliminating the need for manual adjustments and ensuring consistent image quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual adaptation of intensities is used, then the operator can adjust contrast, but the process is time-consuming and may not achieve ideal contrast due to parameter boundaries
Solution Approach 1:
The system automatically determines the intensities of the vascular mask image and component image, and calculates their ratio without operator intervention. The computing unit performs the entire contrast optimization process autonomously, allowing the system to serve itself rather than requiring manual adjustment by the operator.
Solution Approach 2:
The system dynamically changes the intensity parameters of the overlay image by automatically adjusting the intensities of the vascular mask and component images based on calculated ratios. This parameter optimization eliminates the need for manual boundary adjustments and achieves ideal contrast automatically.
2Ease of operation
If manual adaptation of intensities is used, then the operator can control contrast, but the process is complex and requires continuous intervention
Solution Approach 1:
The computing unit automatically performs all contrast optimization operations including determining image intensities, calculating ratios, and adjusting overlay parameters without requiring operator intervention. This automation simplifies the operational process while maintaining optimal contrast.
Solution Approach 2:
The system continuously monitors the intensity ratio between vascular mask and component images and automatically adjusts the overlay parameters to maintain the ideal ratio. This closed-loop feedback mechanism eliminates the need for continuous manual intervention and simplifies the control process.
3Ease of manufacture
If linear weighting method is used, then the images are mixed as a whole, but the contrast ratio cannot be optimized for different image areas
Solution Approach 1:
The system applies different intensity values to different regions of the overlay image by separately determining the intensities of the vascular mask image and component image. This allows optimal contrast to be achieved in both the vascular tree areas and the medical component areas simultaneously, rather than using a uniform weighting across the entire image.
Solution Approach 2:
The system dynamically adjusts the intensity parameters of the individual image components (vascular mask and component image) based on their respective characteristics and the calculated intensity ratio. This selective parameter optimization enables precise contrast control in different image areas while maintaining overall image quality.
Data Source
AI summary
Operating a medical X-ray apparatus to create a fluoroscopy includes capturing a first X-ray image of a vascular tree as a vascular mask, and segmenting the first X-ray image into at least one image area with the vascular tree and at least one image area without the vascular tree. An intensity of the first X-ray image for the image area with the vascular tree is ascertained as a vascular mask intensity. A second X-ray image of a medical component introduced into the vascular tree is created as a component image. An intensity of the second X-ray image for an image area with the medical component is ascertained as a component intensity. A ratio of component intensity and vascular tree intensity is calculated, and an overlay image with the first and the second X-ray image is generated depending on the calculated ratio of the vascular mask intensity and the component intensity.