Differential Sampling Applied to Mammography Image Simulation

Abstract

Differential sampling is a powerful tool that allows Monte Carlo to compute derivatives of responses with respect to certain problem parameters. This capability has been implemented within an in-house Monte Carlo code that simulates detailed mammographic images from two new digital systems. Differential sampling allows for the calculation of the first and all second derivatives of all of the different tallies computed by the code as well as the first and second derivatives of the mammographic image itself with respect to material parameters, such as density and cross sections. The theory behind differential sampling is explained, the methodology for implementation into the imaging code is discussed, and two problems are used to demonstrate the power of differential sampling.