Paper
8 May 1995 Objective measures of quality assurance in a computed radiography-based radiology department
Charles E. Willis, Robert G. Leckie, Jon R. Carter, Morgan P. Williamson, Stephen D. Scotti, Gary S. Norton
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Abstract
Parameters are needed to assess quality assurance in a radiology department where computed radiography (CR) is the principal means of image acquisition. Laser-printed computed radiographs were collected for all patients examined over a period of several days. A sample of 1200 was sorted by subject anatomy and the associated exam information was entered into an EXCEL spreadsheet. Sensitivity (S) numbers were sorted into histogram and analyzed using standard descriptive statistics. Each film was over-read by a board-certified radiologist to assess whether the image was diagnostic and to determine if there were pathologic findings. A significant proportion of images were acquired using inappropriate menu codes. The histogram of S numbers for a given menu code describes a log normal distribution. The S number depends on the technologist's ability to control the technique. A significant proportion of the images were deemed non diagnostic, and many correlated to excessive S numbers. Some were a result of mispositioning. The S number is a valid retrospective measure of radiographic quality assurance. Departments using CR should strive for control on menu codes selected and S numbers produced. Such data should be available from PACS databases.
© (1995) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Charles E. Willis, Robert G. Leckie, Jon R. Carter, Morgan P. Williamson, Stephen D. Scotti, and Gary S. Norton "Objective measures of quality assurance in a computed radiography-based radiology department", Proc. SPIE 2432, Medical Imaging 1995: Physics of Medical Imaging, (8 May 1995); https://doi.org/10.1117/12.208381
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Cited by 10 scholarly publications.
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KEYWORDS
Chest

Chromium

Radiology

Statistical analysis

Spine

Image processing

Quality measurement

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