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Chapter 2:
Applied Linear-Systems Theory
Editor(s): Richard L. Van Metter; Jacob Beutel; Harold L. Kundel
Author(s): Cunningham, Ian A.
Published: 2000
DOI: 10.1117/3.832716.ch2
A wide variety of both digital and nondigital medical-imaging systems are now in clinical use and many new system designs are under development. These are all complex systems, with multiple physical processes involved in the conversion of an input signal (e.g., x rays) to the final output image viewed by the interpreting physician. For every system, a high-quality image is obtained only when all processes are properly designed so as to ensure accurate transfer of the image signal and noise from input to output. An important aspect of imaging science is to understand the fundamental physics and engineering principles of these processes, and to predict how they influence final image quality. For instance, it has been known since the work of Rose [1-€“4], Shaw [5], and others that the image signal-to-noise ratio (SNR) is ultimately limited by the number of quanta used to create the image. This is illustrated in Figure 2.1, showing the improvement in image quality as the number of x-ray quanta used to produce images of a skull phantom is increased from 45 to 6720 quanta/ˆ•mm2. Negligible image noise was added by the imaging system.
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Image processing

Signal processing

Image quality

Signal to noise ratio

Complex systems

Interference (communication)


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