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Improving image quality around subtle lung nodules by reducing artifacts in similar subtraction imaging
Authors:Hitomi Nakamura  Junji Morishita  Yoichiro Shimizu  Yongsu Yoon  Yusuke Matsunobu  Shigehiko Katsuragawa  Hidetake Yabuuchi
Institution:1.Department of Health Sciences, Graduate School of Medical Sciences,Kyushu University,Fukuoka,Japan;2.Department of Health Sciences, Faculty of Medical Sciences,Kyushu University,Fukuoka,Japan;3.Department of Radiological Technology, Faculty of Fukuoka Medical Technology,Teikyo University,Fukuoka,Japan
Abstract:Similar subtraction imaging is useful for the detection of lung nodules; however, some artifacts on similar subtraction images reduce their utility. The authors attempted to improve the image quality of similar subtraction images by reducing artifacts caused by differences in image contrast and sharpness between two images used for similar subtraction imaging. Image contrast was adjusted using the histogram specification technique. The differences in image sharpness were compensated for using a pixel matching technique. The improvement in image quality was evaluated objectively based on the degree of artifacts and the contrast-to-noise ratio (CNR) of the lung nodules. The artifacts in similar subtraction images were reduced in 94% (17/18) of cases, and CNR was improved in 83% (15/18) of cases. The results indicate that the combination of histogram specification and pixel matching techniques is potentially useful in improving image quality in similar subtraction imaging.
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