Accuracies of measuring the artifact index (AI), a quantitative artifact evaluation index in X-ray CT images, were investigated. The AI is calculated based not only on the standard deviation (SD) of the artifact area in the image, but also on the SD of noise components for considering the noise influence. However, conventional measurement methods may not follow this consideration, for example the non-uniformity of the noise distribution is not taken into account, resulting in reducing the accuracy of AI. To address this problem, this study aims to clarify the impact of noise SD measuring (NSDM) error on AI accuracy and improve the accuracy by reducing the NSDM error. Experimental results demonstrated that the conventional noise measurement methods reduced the accuracy of the AI. Specifically, AI inaccuracy due to the NSDM error is severe in the case of weak artifacts and under high noise conditions. Furthermore, the AI accuracy can be improved by reducing the influence of the NSDM error through image smoothing or by correcting NSDM through noise distribution estimation. These results showed that AI can be affected by NSDM errors practically even though it is robust against noise in principle. The impact of NSDM errors must be avoided for reliable artifact evaluation.