Abstract：
:In the UK, physicists and radiographers perform routine quality control (QC) of digital mammography equipment at daily, weekly and monthly intervals. The tests performed and tolerances are specified by standard protocols. The manual nature of many of the tests introduces variability due to the positioning of regions of interest (ROIs) and can be time consuming. The tools on workstations provided by manufacturers limit the range of analysis that radiographers can perform and do not allow for a standard set of tools and analysis because they are specific to a given manufacturer. Automated software provides a means of reducing the variability in the analysis and also provides the possibility of additional, more complex analysis than is currently performed on the daily, weekly and monthly checks by radiographers. To this end, a set of tools has been developed to analyse the routine images taken by radiographers. As well as automatically reproducing the usual measurements by radiographers more complex analysis is provided. A QC image collection system has been developed which automatically routes QC data from a clinical site to a centralised server for analysis. A Web-based interface has been created that allows the users to view the performance of the mammographic equipment. The pilot system obtained over 3000 QC images from seven X-ray units at a single screening centre over 2 years. The results show that these tools and methods of analysis can highlight changes in a detector over time that may otherwise go unnoticed with the conventional analysis.
journal_name
J Digit Imagingjournal_title
Journal of digital imagingauthors
Looney P,Halling-Brown MD,Oduko JM,Young KCdoi
10.1007/s10278-014-9759-zsubject
Has Abstractpub_date
2015-10-01 00:00:00pages
586-93issue
5eissn
0897-1889issn
1618-727Xpii
10.1007/s10278-014-9759-zjournal_volume
28pub_type
杂志文章abstract：:A long-standing challenge of content-based image retrieval (CBIR) systems is the definition of a suitable distance function to measure the similarity between images in an application context which complies with the human perception of similarity. In this paper, we present a new family of distance functions, called att...
journal_title：Journal of digital imaging
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journal_title：Journal of digital imaging
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journal_title：Journal of digital imaging
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更新日期：2011-08-01 00:00:00
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pub_type： 杂志文章,评审
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pub_type： 杂志文章,评审
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journal_title：Journal of digital imaging
pub_type： 杂志文章
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更新日期：2014-08-01 00:00:00
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journal_title：Journal of digital imaging
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更新日期：2012-02-01 00:00:00
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更新日期：2001-03-01 00:00:00
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journal_title：Journal of digital imaging
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更新日期：1998-05-01 00:00:00
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更新日期：2011-10-01 00:00:00
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更新日期：2015-06-01 00:00:00
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journal_title：Journal of digital imaging
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journal_title：Journal of digital imaging
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journal_title：Journal of digital imaging
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