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Image-processing and pattern-recognition methodologies have found a variety of applications in medical imaging and diagnostic radiology. Medical-image processing has been an area of intensive research in the last two decades with remarkable results. A variety of classical methodologies from the signal-processing and pattern-recognition domains and new ones have been implemented and tested for diverse applications. Based on the output, the various approaches can be categorized in one of the three groups shown in the block diagram in Figure 12.1. These groups involve one of the following processes:

Image analysis can be defined as the process where the input to an operator is an image and the output is a measurement. This group includes such processes as automated detection and diagnosis of disease, organ area and volume segmentation, size measurements, and risk estimates [1-6].