A new method to evaluate image quality of CBCT images quantitatively without observers

Yohei Takeshita, Mayumi Shimizu, Kazutoshi Okamura, Shoko Yoshida, Warangkana Weerawanich, Kenji Tokumori, Gainer R. Jasa, Kazunori Yoshiura

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


Objectives: To develop an observer-free method for quantitatively evaluating the image quality of CBCT images by applying just-noticeable difference (JND). Methods: We used two test objects: (1) a Teflon (polytetrafluoroethylene) plate phantom attached to a dry human mandible; and (2) a block phantom consisting of a Teflon step phantom and an aluminium step phantom. These phantoms had holes with different depths. They were immersed in water and scanned with a CB MercuRay (Hitachi Medical Corporation, Tokyo, Japan) at tube voltages of 120 kV, 100 kV, 80 kV and 60 kV. Superimposed images of the phantoms with holes were used for evaluation. The number of detectable holes was used as an index of image quality. In detecting holes quantitatively, the threshold grey value (DG), which differentiated holes from the background, was calculated using a specific threshold (the JND), and we extracted the holes with grey values above DG. The indices obtained by this quantitative method (the extracted hole values) were compared with the observer evaluations (the observed hole values). In addition, the contrast-to-noise ratio (CNR) of the shallowest detectable holes and the deepest undetectable holes were measured to evaluate the contribution of CNR to detectability. Results: The results of this evaluation method corresponded almost exactly with the evaluations made by observers. The extracted hole values reflected the influence of different tube voltages. All extracted holes had an area with a CNR of $1.5. Conclusions: This quantitative method of evaluating CBCT image quality may be more useful and less time-consuming than evaluation by observation.

Original languageEnglish
Article number20160331
JournalDentomaxillofacial Radiology
Issue number3
Publication statusPublished - 2017

All Science Journal Classification (ASJC) codes

  • Otorhinolaryngology
  • Radiology Nuclear Medicine and imaging
  • Dentistry(all)


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