Adaptive Noise Reduction for Low-Dose X-Ray Imaging
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Solution Overview
Problem
Existing noise reduction techniques in low-dose X-ray imaging, such as recursive filtering, struggle with motion blur and ineffective noise reduction due to varying threshold settings, especially when subject motion is present, leading to degraded image quality.
Innovation Solution
A cumulative motion map is used to accumulate noise reduction processing over time, incorporating a statistical value map to adaptively set thresholds based on motion probability, and mix current and previous frames to generate a noise-reduced output image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If recursive filtering is used for noise reduction, then noise is effectively eliminated in stationary subjects, but motion blur occurs and image quality degrades when subject motion is present
Solution Approach 1:
The patent applies dynamics by making the filtering process adaptive rather than static. The recursive filtering is dynamically adjusted based on motion detection results - when motion is detected in a region, the filtering strength is reduced or suspended for that region, while stationary regions continue to receive strong noise reduction. This dynamic adaptation resolves the contradiction between noise reduction effectiveness and motion handling capability.
Solution Approach 2:
The patent implements local quality by applying different processing strategies to different regions of the image based on their motion characteristics. Motion-compensated regions are identified and handled differently from stationary regions, allowing optimal noise reduction for each local area without compromising overall image quality. This localized approach enables simultaneous noise reduction in stationary areas while preserving motion details.
2Ease of operation
If a fixed threshold value is used in recursive filtering to discriminate motion and noise, then the processing is simple, but the threshold cannot be appropriately set due to variations in noise intensity and variance caused by dose conditions, subject density, and motion degree
Solution Approach 1:
The patent transforms the static threshold into a dynamic, adaptive threshold that automatically adjusts based on local image characteristics. The threshold is computed adaptively considering local noise statistics, dose conditions, and motion patterns, eliminating the need for manual threshold setting while maintaining processing simplicity. This adaptive mechanism resolves the contradiction between operational simplicity and detection accuracy.
Solution Approach 2:
The system performs self-service by automatically determining appropriate threshold values without external intervention. The adaptive thresholding mechanism uses local image statistics and motion information to self-adjust the discrimination threshold, making the system autonomous in handling varying noise conditions while maintaining ease of operation.
3Object-affected harmful factors
If low-dose X-rays are used to minimize radiation exposure, then radiation dose is reduced, but quantum mottle increases significantly degrading image quality
Solution Approach 1:
The patent merges multiple frames together through recursive filtering to accumulate signal while averaging out random noise. By combining information from multiple low-dose frames, the effective signal-to-noise ratio is improved, allowing low-dose imaging while maintaining acceptable image quality. This merging approach compensates for the quantum mottle inherent in individual low-dose exposures.
Solution Approach 2:
The recursive filtering process continuously accumulates useful signal information across multiple frames while rejecting random noise. The continuous integration of signal over time maintains image quality despite each individual frame being acquired at low dose, enabling sustained low-dose imaging with acceptable quality.
Data Source
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AI summary
An image processing device for performing noise reduction processing on images obtained by radiation imaging using a recursive way includes: an image input unit that receives frame-by-frame images obtained by the radiation imaging; a motion map generation unit that generates a motion map having motion detection information for each pixel of a difference map obtained by a difference between a current frame image and a previous frame image; a cumulative motion map generation unit that generates a cumulative motion map based on the generated motion map and a cumulative motion map up to a previous frame; a statistical value map generation unit that generates a statistical value map formed by assigning a statistical value representing a motion probability of each pixel of the cumulative motion map; and an output image generation unit that generates an output image of a current frame by mixing the current frame image and the output image of the previous frame based on the cumulative motion map.