Literature DB >> 19560064

Automating quality assurance for digital radiography.

Bruce I Reiner1.   

Abstract

The existing practice of quality assurance (QA) in medical imaging is problematic because of the subjective manner in which it is performed, the lack of community and industry-wide QA standards, a paucity of supporting technology, and an overall lack of accountability. The solution for optimizing QA lies in the creation of objective and reproducible QA metrics, whose analysis can be automated through the creation of computerized QA software algorithms. The QA data derived from these computerized programs would in turn create the infrastructure for a comprehensive QA database, which can serve as a valuable resource for QA education and training, research, decision support, and technology innovation. The ability to objectively track and analyze QA practice across the wide spectrum of imaging providers creates a mechanism for the creation and refinement of objective QA standards and "best practice" guidelines.

Mesh:

Year:  2009        PMID: 19560064     DOI: 10.1016/j.jacr.2008.12.008

Source DB:  PubMed          Journal:  J Am Coll Radiol        ISSN: 1546-1440            Impact factor:   5.532


  15 in total

1.  Application of innovation economics to medical imaging and information systems technologies.

Authors:  Bruce I Reiner; Matthew McKinley
Journal:  J Digit Imaging       Date:  2012-06       Impact factor: 4.056

2.  Continuing challenges in defining image quality.

Authors:  Narendra Shet; Joseph Chen; Eliot L Siegel
Journal:  Pediatr Radiol       Date:  2011-04-14

Review 3.  Creating accountability in image quality analysis part 3: creation of a standardized image-centric mark-up and annotation tool.

Authors:  Bruce I Reiner
Journal:  J Digit Imaging       Date:  2013-08       Impact factor: 4.056

4.  Creating accountability in image quality analysis. Part 4: quality analytics.

Authors:  Bruce I Reiner
Journal:  J Digit Imaging       Date:  2013-10       Impact factor: 4.056

5.  Strategies for radiology reporting and communication : part 4: quality assurance and education.

Authors:  Bruce I Reiner
Journal:  J Digit Imaging       Date:  2014-02       Impact factor: 4.056

6.  A Pilot Study on the Development of Remote Quality Control of Digital Mammography Systems in the NHS Breast Screening Programme.

Authors:  P Looney; M D Halling-Brown; J M Oduko; K C Young
Journal:  J Digit Imaging       Date:  2015-10       Impact factor: 4.056

7.  An Automatic Image Processing Workflow for Daily Magnetic Resonance Imaging Quality Assurance.

Authors:  Juha I Peltonen; Teemu Mäkelä; Alexey Sofiev; Eero Salli
Journal:  J Digit Imaging       Date:  2017-04       Impact factor: 4.056

8.  Innovating through measurement.

Authors:  Bruce I Reiner
Journal:  J Digit Imaging       Date:  2013-02       Impact factor: 4.056

9.  Investigation of the variability in the assessment of digital chest X-ray image quality.

Authors:  Jacquelyn S Whaley; Barry D Pressman; Jonathan R Wilson; Lionel Bravo; William J Sehnert; David H Foos
Journal:  J Digit Imaging       Date:  2013-04       Impact factor: 4.056

Review 10.  Uncovering and improving upon the inherent deficiencies of radiology reporting through data mining.

Authors:  Bruce Reiner
Journal:  J Digit Imaging       Date:  2010-04       Impact factor: 4.056

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