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Transfer functions (TF) are a means for improving the visualization of 3D medical image data. If in addition to intensity another property is employed, two-dimensional TFs can be specified. For this, 2D histograms are helpful. In this work we investigate how the property feature size can be used for the definition of 2D TFs and the visualization of medical image data. Furthermore, we compare this method to approaches that employ gradient magnitude as second property. From our experiments with several medical image data we conclude, that structure size enhanced 2D histograms are more intuitive. This is especially true in the clinical area, where physicians are much more familiar with the meaning of the size of anatomical structures than with the concept of gradient magnitude.