Residual Image Removal in X-ray FPD Systems via Interpolation
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Solution Overview
Problem
Current X-ray imaging systems face impracticalities in storing and calculating numerous correction coefficients for residual image removal due to continuous parameter variations, leading to increased costs and time requirements.
Innovation Solution
An image processing apparatus and method that includes an image acquiring section, a correction coefficient table, a parameter obtaining section, and an interpolator to calculate and apply correction coefficients for residual image removal, using interpolation based on stored coefficients and parameter values such as temperature and storage time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If correction coefficients are stored for all possible parameter combinations (temperature, storage time, etc.), then residual image removal accuracy is improved, but device complexity and memory requirements increase significantly
Solution Approach 1:
The correction coefficient table is segmented into multiple tables, each storing coefficients for specific parameter combinations (temperature ranges, storage time intervals). This segmentation allows the system to manage large numbers of coefficients in an organized, accessible manner without overwhelming memory resources
Solution Approach 2:
Correction coefficients for various parameter combinations are pre-calculated and stored in the correction coefficient table before actual image processing. This preliminary preparation eliminates the need for real-time calculation during operation, reducing processing time and complexity while maintaining accuracy
2Measurement precision
If correction coefficients are calculated for every possible parameter value, then residual image removal accuracy is improved, but processing time and computational resources increase
Solution Approach 1:
Correction coefficients are pre-calculated for various parameter combinations and stored in advance. When processing images, the system simply retrieves the appropriate pre-calculated coefficients based on current parameters, avoiding time-consuming real-time calculations
Solution Approach 2:
The system uses parameter interpolation to calculate correction coefficients for parameter values between those explicitly stored in the table. This allows accurate coefficient determination without pre-calculating and storing coefficients for every possible parameter value
3Measurement precision
If frequent calibration is performed to maintain accurate offset images, then image quality is improved, but productivity and time efficiency decrease
Solution Approach 1:
The system incorporates a feedback mechanism that monitors parameter changes (temperature, storage time) and automatically determines when recalibration is necessary. This selective recalibration approach maintains image quality by performing calibration only when actually needed, rather than on a fixed frequent schedule
Data Source
AI summary
An X-ray imaging system is provided with an FPD and an image processing apparatus. The image processing apparatus is provided with a CPU, a coefficient table, an interpolator and a residual image remover. The CPU acquires an image taken with the FPD. A plurality of coefficients each corresponding to a parameter that changes an attenuation curve are previously stored in the coefficient table. The attenuation curve represents time-varying attenuation of a residual image of the previous image. In a case where the coefficient corresponding to a parameter of the present exposure is not contained in the coefficient table, an appropriate coefficient is calculated by interpolation based on the coefficients contained in the coefficient table. The residual image remover calculates the residual image based on the stored coefficient or the calculated coefficient and a time lapse between the previous and subsequent exposures, and removes the residual image from the present image.