Decomposed Temporal Filtering for X-ray Fluoroscopy Noise Reduction
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Solution Overview
Problem
Digital subtraction in medical imaging enhances noise and reduces the signal-to-noise ratio, particularly in fluoroscopy-guided interventions, leading to poor image quality due to independent imaging noise in mask and current images, and traditional temporal filtering often results in ghosting artifacts from guide wire motion.
Innovation Solution
A decomposed temporal filtering method that separates moving and static structures using a mask image, normalizes contrast, calculates a motion image based on mutual information, and applies temporal filtering only to the residual image, preventing ghosting artifacts while reducing noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If digital subtraction is applied to highlight vessels and guide wire, then vessel location is highlighted, but noise is enhanced and signal-to-noise ratio is reduced
Solution Approach 1:
The patent segments the fluoroscopy image into moving structures (guide wire) and static structures (vessels) using optical flow analysis. This segmentation allows differential processing: temporal filtering is applied only to static structures while moving structures are preserved without filtering, thereby maintaining vessel location information while reducing noise enhancement.
Solution Approach 2:
The patent applies different quality processing to different regions of the image. Static regions (vessels) undergo temporal filtering to reduce noise, while moving regions (guide wire) are preserved with original quality. This local differentiation resolves the contradiction by improving signal-to-noise ratio in static areas without losing information in moving areas.
2Measurement precision
If temporal filtering is applied to reduce noise, then image quality is improved, but ghosting artifacts occur due to guide wire motion
Solution Approach 1:
The patent uses optical flow to segment the image into moving and static components. Temporal filtering is then applied selectively only to the static component (vessels), while the moving component (guide wire) is preserved without filtering. This segmentation eliminates ghosting artifacts caused by filtering moving structures while still achieving noise reduction in static regions.
Solution Approach 2:
The patent dynamically adapts the filtering process by continuously tracking motion through optical flow analysis. The system adjusts which pixels receive temporal filtering based on their motion status, allowing the filtering application to be dynamic rather than static. This resolves the contradiction by preventing ghosting in moving regions while maintaining noise reduction in static regions.
3Loss of information
If mask image is subtracted from current image to highlight guide wire, then guide wire position is visible, but noise from both images is combined
Solution Approach 1:
The patent segments the subtraction image into moving guide wire structures and static vessel structures. By separating these components, the system can apply noise reduction filtering only to the static vessel portions without affecting the guide wire signal. This maintains guide wire position information while reducing the combined noise from mask and current images.
Solution Approach 2:
The patent applies different quality processing to different image regions based on their motion characteristics. Static regions containing vessels receive aggressive noise filtering, while moving regions containing the guide wire are preserved with minimal processing. This local quality approach reduces overall imaging noise while preserving critical guide wire position information.
Data Source
AI summary
A method for temporally filtering medical images during a fluoroscopy guided intervention procedure includes providing a mask image, a fluoroscopy intervention image acquired at a current time during a medical intervention procedure, forming a subtraction image by subtracting the mask image from the intervention image, calculating a motion image of a moving structure in the subtraction image, forming a residual image by subtracting the motion image from the subtraction image, temporally filtering the residual image with a filtered image from a previous time, and adding the motion image to the temporally filtered residual image.