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Beam Optimization for Digital Mammography – II

  • Conference paper
Digital Mammography (IWDM 2006)

Abstract

Optimization of acquisition technique factors (target, filter, and kVp) in digital mammography is required for maximization of the image SNR, while minimizing patient dose. The goal of this study is to compare, for each of the major commercially available FFDM systems, the effect of various technique factors on image SNR and radiation dose for a range of breast thickness and tissue types. This phantom study follows the approach of an earlier investigation [1], and includes measurements on recent versions of two of the FFDM systems discussed in that paper, as well as on three FFDM systems not available at that time. The five commercial FFDM systems tested are located at five different university test sites and include all FFDM systems that are currently FDA approved. Performance was assessed using 9 different phantom types (three compressed thicknesses, and three tissue composition types) using all available x-ray target and filter combinations. The figure of merit (FOM) used to compare technique factors is the ratio of the square of the image SNR to the mean glandular dose (MGD). This FOM has been used previously by others in mammographic beam optimization studies [2],[3]. For selected examples, data are presented describing the change in SNR, MGD, and FOM with changing kVp, as well as with changing target and/or filter type. For all nine breast types the target/filter/kVp combination resulting in the highest FOM value is presented. Our results suggest that in general, technique combinations resulting in higher energy beams resulted in higher FOM values, for nearly all breast types.

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References

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© 2006 Springer-Verlag Berlin Heidelberg

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Williams, M.B. et al. (2006). Beam Optimization for Digital Mammography – II. In: Astley, S.M., Brady, M., Rose, C., Zwiggelaar, R. (eds) Digital Mammography. IWDM 2006. Lecture Notes in Computer Science, vol 4046. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11783237_38

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  • DOI: https://doi.org/10.1007/11783237_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35625-7

  • Online ISBN: 978-3-540-35627-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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