Literature DB >> 15933139

Dose to population as a metric in the design of optimised exposure control in digital mammography.

R Klausz1, N Shramchenko.   

Abstract

This paper describes a method for automatic optimisation of parameters (AOP) in digital mammography systems. Using a model of the image chain, contrast to noise ratio (CNR) and average glandular dose (AGD) are computed for possible X-ray parameters and breast types. The optimisation process consists of the determination of the operating points providing the lowest possible AGD for each CNR level and breast type. The proposed metric for the dose used in the design of an AOP mode is the resulting dose to the population, computed by averaging the AGD values over the distribution of breast types in the population. This method has been applied to the automatic exposure control of new digital mammography equipment. Breast thickness and composition are estimated from a low dose pre-exposure and used to index tables containing sets of optimised operating points. The resulting average dose to the population ranges from a level comparable to state-of-the-art screen/film mammography to a reduction by a factor of two. Using this method, both CNR and dose are kept under control for all breast types, taking into consideration both individual and collective risk.

Mesh:

Year:  2005        PMID: 15933139     DOI: 10.1093/rpd/nch579

Source DB:  PubMed          Journal:  Radiat Prot Dosimetry        ISSN: 0144-8420            Impact factor:   0.972


  5 in total

1.  Optimization of contrast-enhanced spectral mammography depending on clinical indication.

Authors:  Clarisse Dromain; Sandra Canale; Sylvie Saab-Puong; Ann-Katherine Carton; Serge Muller; Eva Maria Fallenberg
Journal:  J Med Imaging (Bellingham)       Date:  2014-12-30

2.  Computing mammographic density from a multiple regression model constructed with image-acquisition parameters from a full-field digital mammographic unit.

Authors:  Lee-Jane W Lu; Thomas K Nishino; Tuenchit Khamapirad; James J Grady; Morton H Leonard; Donald G Brunder
Journal:  Phys Med Biol       Date:  2007-07-30       Impact factor: 3.609

3.  A virtual trial framework for quantifying the detectability of masses in breast tomosynthesis projection data.

Authors:  Stefano Young; Predrag R Bakic; Kyle J Myers; Robert J Jennings; Subok Park
Journal:  Med Phys       Date:  2013-05       Impact factor: 4.071

4.  Characterization of the imaging settings in screening mammography using a tracking and reporting system: A multi-center and multi-vendor analysis.

Authors:  Bruno Barufaldi; Samantha P Zuckerman; Regina B Medeiros; Andrew D Maidment; Homero Schiabel
Journal:  Phys Med       Date:  2020-03-03       Impact factor: 2.685

5.  Dose comparison between screen/film and full-field digital mammography.

Authors:  Gisella Gennaro; Cosimo di Maggio
Journal:  Eur Radiol       Date:  2006-05-30       Impact factor: 7.034

  5 in total

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