A new method for evaluating perceptible contrast information in digital intraoral radiographic systems

Kazutoshi Okamura, Kazunori Yoshiura, Masato Tatsumi, Toshiyuki Kawazu, Toru Chikui, Mayumi Shimizu, Tazuko K. Goto

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Objectives: To evaluate four digital intraoral radiographic systems using perceptibility curves (PCs) in a grayscale domain and to clarify the usefulness of this new method. Methods: Four systems were evaluated, namely the CDR, Dixel, Digora, and Digora Optime. An aluminum phantom with 12 steps was radiographed using all four systems. The mean gray values and their standard deviations were measured for each step as well as the background of the images for each device. The minimum perceptible gray level differences at a given exposure were calculated from the mean gray values and standard deviations, and a PC in the grayscale domain was constructed at each exposure for all devices. The area under the PC was assumed to be the perceptible contrast information at that exposure for each system. By combining the PCs at all exposures for each system, the maximum perceptible contrast information in each system was calculated. The correlation between the perceptible contrast information and the number of perceptible holes by observers at each exposure was examined for all four digital systems. Results: The Dixel and Digora Optime showed similar PCs, and their minimum perceptible gray level differences were the smallest among the systems. The correlation between the number of perceptible holes and the areas under the PCs at each exposure for the four systems was relatively high (r = 0.92). Conclusions: The areas under the PCs in a grayscale domain were highly correlated with observer performance. This method can be used to evaluate the image quality of new digital systems.

Original languageEnglish
Pages (from-to)98-101
Number of pages4
JournalOral Radiology
Volume27
Issue number2
DOIs
Publication statusPublished - Dec 1 2011

All Science Journal Classification (ASJC) codes

  • Radiology Nuclear Medicine and imaging
  • Dentistry (miscellaneous)

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