Statistical texture synthesis of mammographic images with clustered lumpy backgrounds

Realistic anatomical images are useful for assessment and improvement of me dical image quality. The use of synthesized images has the advantage of pro viding the user with a large number of independent samples, in a controlled environment. We propose a method to generate medical textures that are ful ly defined by a set of adjustable parameters and a random number generator, and which statistical properties are analytically tractable. This method, called the "clustered lumpy background", is a generalization of the origina l lumpy background described by Rolland and Barrett (1992). A detailed appl ication of the method in the case of mammography is presented. It is shown that the synthesized images are visually very similar and that their first and second order statistics can be considered as being equivalent. (C) 1999 Optical Society of America.