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The purpose of this study is to develop software for automatic low-contrast object detection in the ACR 464 CT phantom and to evaluate the quantitative effect of radiation dose and object size on low-contrast detectability (LCD). 
Methods: The software was developed using MATLAB R2013a. Thresholds were used to obtain the center of the phantom image (89 HU) and the center of the largest low-object within the phantom (95 HU). The two center coordinates were used as references for detecting other low-contrast objects using template matching. Regions of interest (ROIs) were automatically located within low-contrast objects and in the background, which is at the center of the phantom's image. Mean CT number, noise, contrast, and contrast-to-noise ratio (CNR) were subsequently computed. The low-contrast object detectability threshold was defined as a CNR cut-off of 1. Testing of the algorithm system was carried out on images scanned with various volume CT dose indexes (CTDIvols) of 21.4, 26.8, 32.1, 37.5, 42.8, and 53.6 mGy. The results were compared with a manual method (using micro DICOM viewer software) and statistical analysis of paired sample t-test between the results of automatic and manual methods was carried out. 
Results: The results of the automatic and manual methods show that the minimum resolved object sizes were 5, 5, 4, 4, 4, and 4 mm for CTDIvols of 21.6, 26.8, 32.1, 37.5, 42.8, and 53.6 mGy, respectively. The results revealed that if the diameter of the object increased, the measured CNR increased. An increase in CTDIvol affected the increase in CNR. The CNR measured using automatic and manual methods showed no significant difference (p-value > 0.05). 
Conclusions: An automatic method for detecting low-contrast objects in the ACR 464 CT phantom was successfully completed. Low-contrast detectability was shown to be accurate in test images.