Automating quality assurance for digital radiography.

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.