Abstract: Registration of mammograms is frequently used in computer- aided-detection algorithms, and has been considered for use in the analysis of temporal sequences of screening exams. Previous image registration methods, employing affine transformations or Procrustean transforms based ona small number of fiducial points, have not proven to be entirely adequate. A significantly improved method to facilitate the display and analysis of temporal sequences of mammograms by optimizing image registration and grayscales, has been developed. This involves a fully automatic nonlinear geometric transformation, which puts corresponding skin lines, nipples and chest walls in registration and locally corrects pixel values based on the Jacobian of the transformation. Linear regression is applied between pairs of corresponding pixels after registration, and the derived regression equation is used to equalize grayscales. Although the geometric transformation is not able to correct interior tissue patterns for gross differences in the angle of view or differences resulting from skewing of the breast tissue parallel to the detector, sequences studied have been sufficiently consistent that typically only about 30 percent of images in a sequence are considered to be seriously incompatible with the remaining images. These methods clearly demonstrate a significant benefit for the display and analysis of sequences of digital mammograms. !17
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