On the Information Content of Diagnostic Ultrasound

Echo signals in medical ultrasound are rich in information about tissue composition and structure. But not all of this information is readily apparent from the image. For example, the average size, density and organization of microscopic tissue structures which may be obtained from the first- and second-order statistical properties of the data are difficult to visualize directly from the image. Yet these acoustic parameters have been shown to be sensitive indicators of changes brought on by disease processes in the liver and spleen (Fellingham and Sommer 1984, Insana et al. 1987), and therefore make good classifiying features for tissue characterization. Realizing the full potential of these features requires the use of pattern recognition techniques in order to minimize classification errors due to measurement uncertainty and patient variability.