Radiation Image Movement Detection via Point Spread Function Analysis
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Solution Overview
Problem
Current methods for detecting movement in radiation images, such as X-ray images, face challenges in accuracy due to edge-based detection methods failing to identify blurs in non-edged objects and frequency-based methods struggling to distinguish between movement-induced and structural degradation, leading to reduced detection accuracy and increased re-imaging needs.
Innovation Solution
An image processing apparatus that calculates a point spread function (PSF) from pre-processed radiation images, configures detection regions to isolate movement effects, and evaluates image quality by analyzing the shape of the PSF to determine movement presence, using techniques like iterative back projection and cepstrum analysis to enhance detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If edge-based detection method is used to detect movement, then detection speed is improved, but detection accuracy deteriorates because edges such as bones do not blur during movement
Solution Approach 1:
The patent changes the detection parameter from edge-based features to frequency-based features (high frequency component and low frequency component). This allows detection of movement-induced blur without relying on edges, which do not blur during movement. The method calculates the ratio between high and low frequency components to detect movement accurately.
2Difficulty of detecting and measuring
If frequency-based detection method is used to detect movement, then detection capability is improved, but detection accuracy deteriorates because it is difficult to distinguish between movement-induced degradation and structural cause
Solution Approach 1:
The patent applies local quality by selecting specific regions (lung fields) for frequency analysis. By focusing on regions where movement is most likely to occur and where the structure is relatively uniform, the method can more accurately attribute frequency changes to movement rather than structural variations. This localized approach improves the ability to distinguish movement-induced blur from structural causes.
3Measurement precision
If manual checking of entire image is performed to detect movement, then detection thoroughness is improved, but work efficiency deteriorates
Solution Approach 1:
The patent replaces the manual mechanical checking process with an automated computational system. The image processing apparatus automatically calculates frequency components and detects movement without requiring technician intervention for visual inspection. This substitution maintains detection thoroughness while dramatically improving work efficiency by eliminating manual labor.
4Measurement precision
If manual checking of entire image is performed to detect movement, then detection thoroughness is improved, but time consumption deteriorates
Solution Approach 1:
The patent performs preliminary frequency component calculation and movement detection automatically as part of the image processing workflow, before the technician needs to manually review the image. This preliminary automated action identifies potential movement issues early, allowing the technician to focus only on cases that require manual verification, thereby reducing overall time consumption while maintaining thoroughness.
Data Source
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AI summary
An image processing apparatus includes image acquisition means (101) for acquiring a radiation image capturing an object, function acquisition means (103) for acquiring a point spread function from the radiation image, and determination means (104) for determining, based on a state of the point spread function, presence/absence of a movement of the object in the radiation image.