Reject analysis in direct digital radiography

2012 ◽  
Vol 53 (2) ◽  
pp. 174-178 ◽  
Author(s):  
Eivind Richter Andersen ◽  
Jannike Jorde ◽  
Nadia Taoussi ◽  
Sadia Halima Yaqoob ◽  
Bente Konst ◽  
...  
Keyword(s):  
Digital Radiography ◽  
Reject Analysis

scholarly journals [P104] Digital radiography reject analysis in Dutch hospitals

2018 ◽  
Vol 52 ◽  
pp. 130 ◽  
Author(s):  
Harmen Bijwaard ◽  
Ischa Waard – Schalkx ◽  
Sandra Noij
Keyword(s):  
Digital Radiography ◽  
Reject Analysis

scholarly journals Reject analysis in digital radiography: A local study on radiographers and students’ attitude in Iran

2019 ◽  
Author(s):  
Sajjad Rastegar ◽  
Jalal Beigi ◽  
Ehsan Saeidi ◽  
Ali Dezhkam ◽  
Tofigh Mobaderi ◽  
...  
Keyword(s):  
Digital Radiography ◽  
Local Study ◽  
Reject Analysis

scholarly journals Digital Radiography Reject Analysis: Data Collection Methodology, Results, and Recommendations from an In-depth Investigation at Two Hospitals

2008 ◽  
Vol 22 (1) ◽  
pp. 89-98 ◽  
Author(s):  
David H. Foos ◽  
W. James Sehnert ◽  
Bruce Reiner ◽  
Eliot L. Siegel ◽  
Arthur Segal ◽  
...  
Keyword(s):  
Data Collection ◽  
Digital Radiography ◽  
Analysis Data ◽  
Reject Analysis

scholarly journals Image rejects in general direct digital radiography

2015 ◽  
Vol 4 (10) ◽  
pp. 205846011560433 ◽  
Author(s):  
Bjørn Hofmann ◽  
Tine Blomberg Rosanowsky ◽  
Camilla Jensen ◽  
Kenneth Hong Ching Wah
Keyword(s):  
Image Quality ◽  
Digital Radiography ◽  
Management Training ◽  
Digital Systems ◽  
Imaging Systems ◽  
Radiology Department ◽  
Positioning Errors ◽  
Deletion Rate ◽  
Reject Analysis

Background The number of rejected images is an indicator of image quality and unnecessary imaging at a radiology department. Image reject analysis was frequent in the film era, but comparably few and small studies have been published after converting to digital radiography. One reason may be a belief that rejects have been eliminated with digitalization. Purpose To measure the extension of deleted images in direct digital radiography (DR), in order to assess the rates of rejects and unnecessary imaging and to analyze reasons for deletions, in order to improve the radiological services. Material and Methods All exposed images at two direct digital laboratories at a hospital in Norway were reviewed in January 2014. Type of examination, number of exposed images, and number of deleted images were registered. Each deleted image was analyzed separately and the reason for deleting the image was recorded. Results Out of 5417 exposed images, 596 were deleted, giving a deletion rate of 11%. A total of 51.3% were deleted due to positioning errors and 31.0% due to error in centering. The examinations with the highest percentage of deleted images were the knee, hip, and ankle, 20.6%, 18.5%, and 13.8% respectively. Conclusion The reject rate is at least as high as the deletion rate and is comparable with previous film-based imaging systems. The reasons for rejection are quite different in digital systems. This falsifies the hypothesis that digitalization would eliminates rejects. A deleted image does not contribute to diagnostics, and therefore is an unnecessary image. Hence, the high rates of deleted images have implications for management, training, education, as well as for quality.

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