There is a mystique associated with diagnostic radiology that discourages the use of analysis as a means of understanding and improving radiological examinations. While it is true that intuitive manipulation of the generators and detectors that are available can lead to restricted optimizations, it might also be true that the equipment that is available may not have the correct characteristics. Better optimums may be possible with equipment of different, but state-of-the-art, capabilities or characteristics. This paper presents two cases of modelings for mammography that are examples of this situation. It remains to be established whether or not the modeling has diagnostic significance. However, since the conclusions appear to be significant it seems important to pursue such projects. To accomplish this, it is necessary to generate information and data that can be useful to the modelings. The extensive imaging research that has recently occupied many diagnostic radiological physicists is only part of the necessary information. More emphasis needs to be given to research that is useful in helping to describe the details of the x-ray photon image. One of the examples of modeling that is discussed is related to signal-to-noise ratios for the detection of calcifications in mammography. The other is a study of contrast in magnification mammography.