Radiation Imaging Noise Suppression via Template Contribution Rates
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Solution Overview
Problem
Existing radiation imaging technologies face challenges in detecting specific regions quickly and accurately due to noise interference in radiation images, particularly during medical treatments, where real-time noise suppression is necessary.
Innovation Solution
A radiation imaging apparatus that uses a template image's principal components to calculate contribution rates for both the template and radiation images, allowing for rapid detection of specific regions by matching these rates, thereby suppressing noise effects without performing principal component analysis on the new radiation image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If principal component analysis is performed on multiple images at different resolution levels to remove noise, then noise removal accuracy is improved, but processing time increases making real-time detection impossible
Solution Approach 1:
The patent performs principal component analysis on template images in advance to extract contribution rates, storing these results for later use. During actual detection, only contribution rate acquisition and matching are performed on new radiation images, avoiding repeated PCA computations. This preliminary preparation of contribution rates enables real-time noise suppression without sacrificing accuracy.
Solution Approach 2:
The patent uses template images that are processed in advance to create contribution rate models, which are then copied and applied to multiple new radiation images. Instead of performing PCA on each new image, the pre-computed contribution rates from templates are reused, significantly reducing processing time while maintaining consistent noise removal quality across all detections.
2Measurement precision
If principal component analysis is performed on each new radiation image to remove noise, then noise suppression is improved, but detection speed decreases
Solution Approach 1:
The system pre-computes contribution rates from template images before actual detection begins. During real-time detection of new radiation images, only the lightweight operation of acquiring contribution rates and performing matching is required, eliminating the computationally intensive PCA step from the detection workflow while preserving noise suppression quality.
Solution Approach 2:
The patent transforms the detection problem from performing PCA on raw images to working with pre-extracted contribution rates. By changing the parameter space from full images to contribution rate coefficients, the computational complexity is dramatically reduced, enabling fast detection while maintaining the ability to suppress noise effectively through the matching process.
3Measurement precision
If multiple images at different resolutions are used for principal component analysis, then noise removal accuracy is improved, but device complexity increases
Solution Approach 1:
The patent performs the complex operation of acquiring images at multiple resolution levels and performing principal component analysis only once on template images during setup. The resulting contribution rates are stored and reused for all subsequent detections, converting a complex per-image process into a simple per-detection process that only involves contribution rate matching.
Data Source
AI summary
A radiation imaging apparatus includes an irradiation element that irradiates a radiation, a radiation detection, an image generation element that generates a radiation image, a memory element that stores a principal component and a location detection element that detects and extracts a specific region from the radiation image by a matching using each contribution rate relative to each template image and each radiation image.