Academic Press, 1996. — 702 p.
This book is an outgrowth of a course that the authors have taught since 1974 at the Optical Sciences Center at the University of Arizona. The students in this course have been advanced graduate students, most of them majoring in optical sciences, but some in physics, mathematics, or electrical engineering. The course is intended to serve two purposes. The first and most obvious is to prepare the student to do research in radiological imaging. The second (and perhaps more important) function is to teach general image science within a radiographic context, to help the student gain fluency with the essential analytical tools of linear systems theory and the theory of stochastic processes that are applicable to any imaging system, radiographic or otherwise.
We have tried to maintain that dual purpose in this book as well. While the specific systems being analyzed are medical diagnostic systems, the principles involved are far broader. To be able to calculate a modulation transfer function or to determine the signal-to-noise ratio in a processed image is a necessary skill for anyone involved in image formation, detection, or processing, whatever the nature of the radiation.
The Clinical Setting
Theory of Linear Systems
Theory of Random Processes
Application of Linear Systems Theory to Radiographic Imaging
Detectors
Classical Tomography
Computed Tomography
Multiplex Tomography
Three-Dimensional Imaging
Noise in Radiographic Images
Scattered Radiation
A: The Dirac Delta Function
B: The Fourier Transform
C: Interaction of Photons with Matter
D: Radiation Quantities