Abstract
It has been shown that dual-screen image acquisition technique can be used to improve the image signal-to-noise ratio (SNR) in computed radiography (CR) imaging. In chest imaging situations, acquisition with a high resolution (HR) screen and a standard resolution (ST) screen can also be used to improve the modulation transfer function. Unlike in conventional radiography using two screens, the front and back images in dual-screen CR imaging can be separately read out and superimposed with the weighting factors selected to optimize a specific image quality descriptor. The purpose of this paper is to determine the weighting method which would optimize the frequency dependent detective quantum efficiency (DQE) in dual-screen CR imaging with an HR and a ST screen. A theoretical model is derived to relate the DQE in the superimposed image to those in the front and back images and to determine the optimal weighting factors and the maximum DQE that can be achieved. Using this model and DQEs measured for the HR and ST screens, we could estimate optimal weighting factors and maximum DQEs as a function of frequency. Various screen combinations were studied and compared for the maximum DQE that can be achieved. We have shown that for maximum DQE, the front and back images should be weighted in such a way that their magnitudes are proportional to the DQE divided by the MTF. The maximum DQE in the optimally superimposed image is equal to the sum of the DQEs of the front and back images.
Original language | English (US) |
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Pages (from-to) | 684-694 |
Number of pages | 11 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 3336 |
DOIs | |
State | Published - 1998 |
Event | Medical Imaging 1998: Physics of Medical Imaging - San Diego, CA, United States Duration: Feb 22 1998 → Feb 24 1998 |
Keywords
- Computed radiography
- Detective quantum efficiency
- Dual-screen imaging
- Optimization
- Storage phosphors
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering