During the acquisition of a mammogram the breast is compressed between the compression paddle and the support table. When compression is applied, the upper plate is tilted which results in variation in breast thickness from the chest wall to the breast margin. Variation in breast thickness influences the grey-level values of the image and hampers image analysis, such as volumetric breast density estimation. In this paper, we present and compare two methods that estimate and correct image tilt. The first method estimates tilt from fatty tissue regions. The second method is based on the entropy of the grey-level distribution of the image. Both methods use a classifier that distinguishes fatty areas from dense tissue based on texture features independent of tilt. The tilt correction methods are evaluated by assessing their accuracies in estimating artificial tilts that are added to images that are known to have only a small tilt. On average, both methods are able to estimate the artificial tilt. To the best of our knowledge, this is the first paper that presents and validates tilt correction methods on individual mammograms.