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Improvement of signal‐to‐noise and contrast‐to‐noise ratios in dual‐screen computed radiography
Author(s) -
Shaw Chris C.,
Wang TienPeng,
Breitenstein Darryl S.,
Gur David
Publication year - 1997
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.598151
Subject(s) - contrast to noise ratio , computed radiography , signal to noise ratio (imaging) , image quality , medical imaging , radiography , mammography , computer science , noise (video) , nuclear medicine , optics , artificial intelligence , image (mathematics) , physics , medicine , radiology , cancer , breast cancer
A dual‐screen computed radiography (CR) technique has been developed to improve and optimize the overall image signal‐to‐noise ratio (SNR) and contrast‐to‐noise ratio (CNR). With this technique, two CR screens are exposed together and separately scanned to form a front and a back image. These two images are then superimposed to form an image of improved SNR and CNR. A mathematical model has been derived to describe the improvement and optimization of the SNR and CNR. Based on this model, the front and back images should be weighted in proportion to their SNR squared to optimize the SNR of the composite image. Imaging experiments have been conducted to verify the theoretical model under mammographic and chest imaging conditions. The results largely agree with the theoretical predictions. It has also been found that optimization of the SNR results in nearly optimal CNR and vice versa. For mammographic imaging, a 14%–22% improvement in the SNR and a 13%–19% improvement in the CNR have been demonstrated. For chest imaging, a 31%–36% improvement in the SNR and a 28%–30% improvement in the CNR has been demonstrated.