How is noise quantified in CT imaging?

In CT imaging, noise is quantified by obtaining the standard deviation within a region of interest (ROI). This approach is effective because noise in an image typically manifests as variations in pixel values, and the standard deviation serves as a statistical measure that reflects the variability or spread of those values. A higher standard deviation indicates greater variability in pixel intensity, which correlates with increased noise levels in the image. This method allows for a precise assessment of the noise present in the imaging data, helping radiologists and technicians understand the overall quality and clarity of the scanned images.

Other methods, such as measuring total energy absorbed, maximum pixel value, or applying filters, do not directly provide a quantifiable measure of noise levels in the same way. While these methods might be relevant for other aspects of image quality or correction, they do not specifically capture the statistical variations that define noise. Thus, using standard deviation in an ROI remains a standard practice for accurately quantifying noise in CT imaging.