Journal de radiologie OMICS

Abstrait

Redefining Image Quality Analysis

Bruce Reiner

Quality assurance in medical imaging is dependent upon multiple steps in the collective imaging chain; including image quality analysis, which defines the diagnostic capabilities of the imaging dataset. Conventional methods used for image quality analysis primarily fall into two categories; operator-performed analysis using subjective numerical scoring of perceived image quality and computerized analysis using objective measurements correlating with the human visual system. A number of deficiencies exist in these conventional methods; which often fail to take into account clinical context, patient attributes, and data segmentation. The incorporation of these variables into an alternative standardized methodology for image quality analysis would have the potential to expand the practicality, utility, and granularity of image quality analysis; while leading to the creation of a referenceable database with real-time decision support applications.