Detection and discrimination using x-radiation

This paper examines the fundamental principles underlying X-ray imaging, describes several critical issues concerning these systems, and indicates areas in which neural network methods may be expected to be important. Special attention is paid to relatively sophisticated techniques such as reconstruction imaging and multiple-energy imaging, and several concepts from imaging science are described. New modalities such as phase imaging and coherent scatter imaging are introduced. Neural network methods have significant potential utility for the operation and evaluation of X-ray imaging systems. In addition they should prove vitally important for the analysis of the tremendous quantities of data which these systems generate. These conclusions are equally applicable to other types of imaging, including nuclear tracer, magnetic resonance and ultrasound