1. A method for at least one of masking and identifying a noisy background area an intensity-value-coded image, the method comprising: generating a background mask for the intensity-value-coded image by generating an intensity value histogram of the image; fitting a model curve to a subarea of the intensity value histogram related to background noise; calculating a threshold value in the intensity value histogram from fit parameters of the model curve, the threshold value separating the subarea of the intensity value histogram related to the background noise from a subarea of the intensity value histogram related to an anatomical structure; and generating the background mask, starting from at least one defined image area belonging to the background noise, by adding all pixels having intensities below the threshold value to the background mask and all pixels connected to the at least one defined image area via pixels also having intensities below the threshold value; at least one of masking the intensity-value-coded image using the generated background mask and identifying the noisy background area in the intensity-value-coded image using the background mask, generating a modified background mask for the intensity-value-coded image from the generated background mask by combining topographically coherent pixels that are not covered by the generated background mask to form at least one cluster, and adding at least one cluster to the modified background mask as a function of a mean intensity value of the at least one cluster.