Purpose: To compare the methods of automated noise measurement at the polyester resin (PESR) phantom images and clinical abdominal images. Method: The PESR phantom was scanned with a Siemens SOMATOM Emotion 6 CT scanner for various tube voltages, i.e., 80, 110, and 130 kV. Noises from images of the PESR phantom and 27 clinical abdominal scans were automatically measured. The methods used for automatic measurements were methods proposed by Christianson et al (2015), Malkus et al (2017), and Anam et al (2019), respectively. Results: Three methods of automatic noise measurements can distinguish the noise of the three tube voltages. The measured noises from three methods decrease with increasing tube voltage. It can also be seen that the highest noise in PESR phantom images is Christianson et al (2015) method, and the smallest noise is Malkus et al (2017) method. The highest noise in clinical abdominal images is Malkus et al (2017) method, and the smallest noise is Anam et al (2019) method. Conclusion: The algorithms to automatically measure noises proposed by Christianson et al (2015), Malkus et al (2017), and Anam et al (2019) have been compared. Although the three methods can distinguish noise for different exposure factors, the magnitude of the noise from the three methods can vary. Until now there is no standard for automatic noise determination.