A statistical-based automatic detection of a low-contrast object in the ACR CT phantom for measuring contrast-to-noise ratio of CT images.

Abstract

Purpose. This study aimed to develop a new method for automated contrast-to-noise ratio (CNR) measurement using the low-contrast object in the ACR computed tomography (CT) phantom.Methods. The proposed method for CNR measurement was based on statistical criteria. A region of interest (ROI) was placed in a specific radial location and was then rotated around 360° in increments of 2°. At each position, the average CT number within the ROI was calculated. After one complete rotation, a profile of the average CT number around the full rotation was obtained. The center coordinate of the low-contrast object was determined from the maximum value of the profile. The CNR was calculated based on the average CT number and noise within the ROI in the low-contrast object and the ROI in the background, i.e., at the center of the phantom. The proposed method was used to evaluate CNR from images scanned with various phantom rotations, images with various noise levels (tube currents), and images from 25 CT scanners. The results were compared to a previous method based on a threshold approach.Results. The proposed method successfully placed the ROI properly in the center of a low-contrast object for variations of phantom rotation and tube current, whereas was not properly located in the center of the low-contrast object using the previous method. In addition, from 325 image samples of the 25 CT scanners, the proposed method successfully (100%) located the ROI within the low-contrast objects of all images used. The success rate of the previous method was only 58%.Conclusion. A new method for measuring CNR in the ACR CT phantom has been proposed and implemented. It is more powerful than a previous method based on a threshold approach.