Digital camera resolution and proximal caries detection.
OBJECTIVE
To evaluate the diagnostic accuracy of proximal caries detection from digitized film images captured by a digital camera at different resolution settings.


METHODS
Twenty-five periapical radiographs of 50 premolar and 25 molar teeth were photographed using a digital camera, Sony Cyber-shot, DSC-S75 at three different resolution settings: 640 x 480, 1280 x 960 and 1600 x 1200. Seventy-five digital images were transferred to a computer, saved and opened using ACDSee software. In addition, a PowerPoint slide was made from each digital image. Five observers scored three groups of images (the films, the displayed 1:1 digital images on the ACDSee software, and the PowerPoint slides) for the existence of proximal caries using a 5-point confidence scale, and the depth of caries on a 4-point scale. Ground sections of the teeth were used as the gold standard. Az values under the receiver operating characteristic (ROC) curve of each group of images and at different resolutions were compared using the Friedman and Wilcoxon signed rank tests. Mean different values between the lesions' depth interpreted by the observers and that of the gold standard were analysed.


RESULTS
Films showed the highest Az values. Only the 1280 x 960 images on the ACDSee software showed no significant difference of the Az value from the films (P=0.28). The digital images from three resolution settings on the PowerPoint slides showed no significant differences, either among each other or between them and the films. For caries depth, the 1280 x 960 images showed lower values of mean difference in enamel lesions compared with the other two resolution groups.


CONCLUSIONS
This study showed that in order to digitize conventional films, it was not necessary to use the highest camera resolution setting to achieve high diagnostic accuracy for proximal caries detection. The 1280 x 960 resolution setting of the digital camera demonstrated comparable diagnostic accuracy with film and was adequate for digitizing radiographs for caries detection.
Prapayasatok
S
S
Department of Oral Radiology, Faculty of Dentistry, Chiang Mai University, Chiang Mai 50200, Thailand. sangsom@chiangmai.ac.th
Janhom
A
A
Verochana
K
K
Pramojanee
S
S
D001641:Bicuspid; D003731:Dental Caries / Q000000981:diagnostic imaging*; D006801:Humans; D008963:Molar; D015588:Observer Variation; D012372:ROC Curve; D019252:Radiography, Dental, Digital / Q000295:instrumentation*; D012984:Software; D018709:Statistics, Nonparametric; D014962:X-Ray Film