
Proceedings Paper
Dual-energy contrast enhanced digital mammography using a new approach for breast tissue cancelingFormat | Member Price | Non-Member Price |
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Paper Abstract
In this study, we propose a novel approach to dual-energy
contrast-enhanced digital mammography, with the development of a
dual-energy recombination algorithm based on an image chain model
and the determination of the associated optimal low and high-energy
techniques. Our method produces clutter-free iodine-equivalent
images and includes thickness correction near the breast border.
After the algorithm description, the optimal low and high-energy
acquisition techniques are determined to obtain a compromise between
image quality and glandular dose. The low and high-energy techniques
were chosen to minimize the glandular dose for a target Signal
Difference to Noise Ratio (SDNR) in the dual-energy recombined
image. The theoretical derivation of the iodine SDNR in the
recombined image allowed the prediction of the optimal low and
high-energy techniques. Depending on the breast thickness and
glandular percentage, the optimal low-energy kVp and mAs ranged from
24kVp (Mo/Mo or Mo/Rh) to 35kVp (Rh/Rh), and from 60 to 90mAs
respectively, and the high-energy kVp and mAs ranged from 40kVp to
47kVp (Mo/Cu), and from 80mAs to 290mAs. We proved the better
performance of our algorithm compared to the classic weighted
logarithmic subtraction method in terms of patient dose and also in terms of texture
cancelation, through the use of artificial textured images. Values of iodine contrast measured on phantom were
close to the expected iodine thickness. Good correlation was found
between the measured and theoretical iodine SDNR in the dual-energy
images, which validates our theoretical optimization of the
acquisition techniques.
Paper Details
Date Published: 21 March 2007
PDF: 12 pages
Proc. SPIE 6510, Medical Imaging 2007: Physics of Medical Imaging, 65102H (21 March 2007); doi: 10.1117/12.710133
Published in SPIE Proceedings Vol. 6510:
Medical Imaging 2007: Physics of Medical Imaging
Jiang Hsieh; Michael J. Flynn, Editor(s)
PDF: 12 pages
Proc. SPIE 6510, Medical Imaging 2007: Physics of Medical Imaging, 65102H (21 March 2007); doi: 10.1117/12.710133
Show Author Affiliations
Sylvie Puong, Univ. Paris XI (France)
GE Healthcare (France)
Xavier Bouchevreau, Altran (France)
Fanny Patoureaux, GE Healthcare (France)
GE Healthcare (France)
Xavier Bouchevreau, Altran (France)
Fanny Patoureaux, GE Healthcare (France)
Published in SPIE Proceedings Vol. 6510:
Medical Imaging 2007: Physics of Medical Imaging
Jiang Hsieh; Michael J. Flynn, Editor(s)
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