Abstract
Several low-dose images are necessary to obtain an image that can be used for diagnosis. However, it is clinically undesirable to expose a patient to multiple exposures in order to obtain an optimal image. The purpose of this study was to simulate a low-dose image from the image generated by a routine dose. Images of acrylic steps were obtained using multiple doses in digital mammography with computed radiography to generate additional noise. This noise was added to take into account the resolution of the X-ray detector using the some filters. The image simulated using the filter based on the WS was similar to an actual low-dose image. The image simulated using the presampled MTF filter was less similar to an actual low-dose image. By using the proposed method, we were able to obtain a simulated low-dose image from an image generated by a routine dose.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Båth, M., Håkansson, M., Tingberg, A., Månsson, L.G.: Method of simulating dose reduction for digital radiographic systems. Radiation Protection Dosimetry 114, 253–259 (2005)
Veldkamp, W.J.H., Kroft, L.J.M., Pieter, J., Delft, A.V., Geleijns, J.: A Technique for Simulating the Effect of Dose Reduction on Image Quality in Digital Chest Radiography. Journal of Digital Imaging 22(2), 114–125 (2009)
The Central Committee on Quality Control of Mammographic Screening in Japan, Digital mammography quality control manual (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Saito, Y., Kawai, A., Fujita, N., Yamada, M., Kodera, Y. (2012). Reduction of Patient Dose in Digital Mammography: Simulation of Low-Dose Image from a Routine Dose. In: Maidment, A.D.A., Bakic, P.R., Gavenonis, S. (eds) Breast Imaging. IWDM 2012. Lecture Notes in Computer Science, vol 7361. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31271-7_79
Download citation
DOI: https://doi.org/10.1007/978-3-642-31271-7_79
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-31270-0
Online ISBN: 978-3-642-31271-7
eBook Packages: Computer ScienceComputer Science (R0)