Beam optimization for digital mammography - II

Mark B. Williams, Priya Raghunathan, J Anthony Seibert, Alex Kwan, Joseph Lo, Ehsan Samei, Laurie Fajardo, Andrew D A Maidment, Martin Yaffe, Aili Bloomquist

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations


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, MOD, 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.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number of pages8
Volume4046 LNCS
StatePublished - 2006
Event8th International Workshop on Digital Mammography, IWDM 2006 - Manchester, United Kingdom
Duration: Jun 18 2006Jun 21 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4046 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349


Other8th International Workshop on Digital Mammography, IWDM 2006
Country/TerritoryUnited Kingdom

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science


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