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  • Title: Quality assurance of computed and digital radiography systems.
    Author: Walsh C, Gorman D, Byrne P, Larkin A, Dowling A, Malone JF.
    Journal: Radiat Prot Dosimetry; 2008; 129(1-3):271-5. PubMed ID: 18319281.
    Abstract:
    Computed radiography (CR) and digital radiography (DR) are replacing traditional film screen radiography as hospitals move towards digital imaging and picture archiving and communication systems (PACS). Both IPEM and KCARE have recently published quality assurance and acceptance testing guidelines for DR. In this paper, the performance of a range of CR and DR systems is compared. Six different manufacturers are included. Particular attention is paid to the performance of the systems under automatic exposure control (AEC). The patient is simulated using a range of thicknesses of tissue equivalent material. Image quality assessment was based on detector assessment protocols and includes pixel value measures as well as subjective assessment using Leeds Test Objects. The protocols for detector assessment cover a broad range of tests and in general detectors (whether DR or CR) performed satisfactorily. The chief limitation in performing these tests was that not all systems provided ready access to pixel values. Subjective tests include the use of the Leeds TO20. As part of this work, suggested reference values are provided to calculate the TO20 image quality factor. One consequence of moving from film screen to digital technologies is that the dynamic range of digital detectors is much wider, and increased exposures are no longer evident from changes in image quality. As such, AEC is a key parameter for CR and DR. Dose was measured using a standard phantom as a basic means of comparing systems. In order to assess the AEC performance, exit doses were also measured while varying phantom thickness. Signal-to-noise ratios (SNRs) were calculated on a number of systems where pixel values were available. SNR was affected by the selection of acquisition protocol. Comparisons between different technologies and collation of data will help refine acceptance thresholds and contribute to optimising dose and image quality.
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