Abstract
Classical medical imaging research has concentrated on new imaging technologies, on methods for improving image quality, and on techniques for extracting clinically useful parameters from images. Relatively little attention has been given to combining imaging systems with methods for interpreting clinical data. The emergence of expert systems has raised the possibility that imaging techniques can be integrated with tools for clinical decision making and problem solving. Five general schemes for combining these technologies are discussed. The interpretation of biomedical images is particularly problematic because of statistical, structural and temporal variation in morphology. Particular attention is paid to the processes which are needed to transform a pixel array into a symbolic form suitable for interpretation of the morphology. Some ways in which knowledge of shape, structure, and object taxonomy may contribute to the interpretation are discussed.
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© 1988 Springer-Verlag Berlin Heidelberg
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Fox, J., Walker, N. (1988). Knowledge Based Interpretation of Medical Images. In: Viergever, M.A., Todd-Pokropek, A. (eds) Mathematics and Computer Science in Medical Imaging. NATO ASI Series, vol 39. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-83306-9_10
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DOI: https://doi.org/10.1007/978-3-642-83306-9_10
Publisher Name: Springer, Berlin, Heidelberg
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