Adapting clinical images to appear with different noise and sharpness to model a different detector

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Abstract

Comparing the clinical performance of digital mammography technologies is challenging. The aim of this work is to develop and test a methodology for adjusting mammographic images taken on a given imaging system to simulate their appearance as if taken on a different system. Such methodology would be very useful for a wide range of system performance and design studies using both phantom and clinical images. The process involves changing the image blurring in accordance with the measured modulation transfer functions and adding noise (electronic, quantum and structure). The method has been tested by adapting flat field images acquired using an amorphous selenium detector and a computed radiography (CR) detector to different dose levels and comparing the resultant simulated NPSs with directly measured NPSs. For the detectors used in this work the NPSs at different dose levels are well predicted. This could be a powerful tool for studies of clinical image quality. © 2010 Springer-Verlag.

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Mackenzie, A., Workman, A., Dance, D. R., Yip, M., Wells, K., & Young, K. C. (2010). Adapting clinical images to appear with different noise and sharpness to model a different detector. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6136 LNCS, pp. 319–326). https://doi.org/10.1007/978-3-642-13666-5_43

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