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Proceedings Paper

Tools and methods for exposure control optimization in digital mammography in presence of texture
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Paper Abstract

To accurately detect radiological signs of cancer, mammography requires the best possible image quality for a target patient dose. The application of automatic optimization of parameters (AOP) to digital systems has been improved recently. The metric used to derive this AOP was based on the expected CNR of calcium material in a uniform background. In this work, we use a new metric, based on the detection performance of an a-contrario observer on lesions in simulated images. Breast images at various thicknesses and glandularity levels were simulated with flat and textured backgrounds. Various exposure spectra (Mo/Mo, Mo/Rh and Rh/Rh anode/filter materials, kVp ranging from 25 to 33 kV) were considered. The tube output has been normalized in order to obtain comparable AGD values for each image of a given breast over the various acquisition techniques. Images were scored with the a-contrario observer, the performance criterion being the minimal lesion size needed to reach a given detection threshold. The optimal spectra are found similar to those delivered by the AOP in both flat and textured backgrounds. The choice of the anode/filter combination appears to be more critical than kVp adjustments in particular for the thicker breasts. Our approach also yields an estimate of the detection variability due to texture signal. We found that the anatomical structure variability cannot be overcome by beam quality optimization of the current system in presence of complex background, which confirms the potential benefit of any imaging technology reducing the variability of detection due to texture.

Paper Details

Date Published: 8 March 2007
PDF: 12 pages
Proc. SPIE 6515, Medical Imaging 2007: Image Perception, Observer Performance, and Technology Assessment, 651518 (8 March 2007); doi: 10.1117/12.709797
Show Author Affiliations
Bénédicte Grosjean, Ecole Centrale Paris (France)
GE Healthcare France (France)
Serge Muller, GE Healthcare France (France)
Henri Souchay, GE Healthcare France (France)


Published in SPIE Proceedings Vol. 6515:
Medical Imaging 2007: Image Perception, Observer Performance, and Technology Assessment
Yulei Jiang; Berkman Sahiner, Editor(s)

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