ArticleOral radiology2023
Relationship between image information content and observer performance in digital intraoral radiography.
Article in Oral radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
6 authors at 4 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
objectivesThis study conducted a receiver operating characteristic (ROC) analysis by applying improved cluster signal-to-noise (CSN) analysis to digital intraoral radiographs and develop an observer-free method of analyzing image quality related to the observer performance in the detection task.
methodsTwo aluminum step phantoms with a thickness interval of 1.0 mm were used for this study. One phantom had holes of increasing depth (from 0.05 to 0.35 mm) and the other had no holes. Phantom images were obtained under various exposure dose and image capture modes using a dental X-ray unit, a photostimulable phosphor imaging plate, and scanner system. These phantom images were analyzed using the FindFoci plugin in ImageJ software. Subsequently, true positive rates (TPRs) and false positive rates (FPRs) were calculated by analyzing phantom images with and without holes. We constructed ROC curves by plotting the TPRs against the FPRs and calculated the area under the ROC curve (AUC). Using the same phantom images with holes, eight observers assessed the number of detectable holes. Correlations between observer detection performance and AUC values were evaluated.
resultsAUC values increased as the exposure dose increased and showed different tendencies depending on the image capture mode. The AUC values showed a high correlation with observer detection performance (r = 0.76).
conclusionsAUC values obtained from CSN analysis reflect image quality and replace the observer detection performance test of image quality.
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