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Proceedings Paper

Observer model optimization of a spectral mammography system
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Paper Abstract

Spectral imaging is a method in medical x-ray imaging to extract information about the object constituents by the material-specific energy dependence of x-ray attenuation. Contrast-enhanced spectral imaging has been thoroughly investigated, but unenhanced imaging may be more useful because it comes as a bonus to the conventional non-energy-resolved absorption image at screening; there is no additional radiation dose and no need for contrast medium. We have used a previously developed theoretical framework and system model that include quantum and anatomical noise to characterize the performance of a photon-counting spectral mammography system with two energy bins for unenhanced imaging. The theoretical framework was validated with synthesized images. Optimal combination of the energy-resolved images for detecting large unenhanced tumors corresponded closely, but not exactly, to minimization of the anatomical noise, which is commonly referred to as energy subtraction. In that case, an ideal-observer detectability index could be improved close to 50% compared to absorption imaging. Optimization with respect to the signal-to-quantum-noise ratio, commonly referred to as energy weighting, deteriorated detectability. For small microcalcifications or tumors on uniform backgrounds, however, energy subtraction was suboptimal whereas energy weighting provided a minute improvement. The performance was largely independent of beam quality, detector energy resolution, and bin count fraction. It is clear that inclusion of anatomical noise and imaging task in spectral optimization may yield completely different results than an analysis based solely on quantum noise.

Paper Details

Date Published: 18 March 2010
PDF: 12 pages
Proc. SPIE 7622, Medical Imaging 2010: Physics of Medical Imaging, 762210 (18 March 2010); doi: 10.1117/12.845480
Show Author Affiliations
Erik Fredenberg, Royal Institute of Technology (Sweden)
Magnus Åslund, Sectra Mamea AB (Sweden)
Björn Cederström, Royal Institute of Technology (Sweden)
Mats Lundqvist, Sectra Mamea AB (Sweden)
Mats Danielsson, Royal Institute of Technology (Sweden)


Published in SPIE Proceedings Vol. 7622:
Medical Imaging 2010: Physics of Medical Imaging
Ehsan Samei; Norbert J. Pelc, Editor(s)

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