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

Abstract

This quantitative method of evaluating CBCT image quality may be more useful and less time-consuming than evaluation by observation.

Cluster signal-to-noise analysis for evaluation of the information content in an image

“…Test object A Teflon (polytetrafluoroethylene) plate phantom of 1-mm thickness simulating bone 11 was used in this study (Figure 1a). The phantom contained 84 holes that are arranged in 7 rows by 12 columns.…”

“…We received all images from Takeshita's study. 11 The images were prepared in that study as follows. All CBCT image series in axial planes were reconstructed onto new planes that were parallel to the surface of the phantom.…”

“…Relationship among cluster signal-to-noise analysis, Takeshita's method 11 and observer performance: In cluster signal-to-noise analysis, FPRs of observers corresponding to the detected signals (TPRs) were obtained using cluster signal-to-noise curves and observers' data. First, each detected signal from observers' data was converted into the corresponding FPR one by one using cluster signal-to-noise curves as conversion graphs.…”

“…If the mean FPR of all images exceeded the curve, the maximum TPR of that curve was used as the calculated TPR instead of recalculating. In Takeshita's method, 11 cut-off values (ΔG) are determined for each column of holes in the image. These 12 cut-off values were applied in the FindFoci plugin of ImageJ in the same way as for cluster signal-to-noise analysis.…”

“…It may be less time consuming and more reliable if a new method excluding observers can be developed to simulate observer performance. Takeshita et al 11 introduced a new observer-free method of evaluating image quality. However, they used a limited number of threshold gray values.…”