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Non-stationary spatial filtering and accelerated curve fitting for parametric imaging with dynamic PET

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Abstract

A non-stationary spatial low pass filter was developed and implemented in combination with an accelerated non-linear curve fitting routine to create low noise-high contrast images of physiological parameters with dynamic positron emission tomography. The method was applied to 18F-2-fluoro-2-deoxyglucose (FDG) studies, and images of local blood volume, kinetic rate constants, precursor pool volume and glucose metabolism were generated. Noise reduction and contrast preservation was demonstrated in a simulated pie phantom and a study of a patient with a recent brain infarct. Considerably improvement in quantitative accuracy of pixel parameter values was observed in the phantom study in comparison with unprocessed or conventionally smoothed images.

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Authors and Affiliations

  1. Max-Planck-Institut für neurologische Forschung, Joseph-Stelzmann-Strasse 9, D-5000, Köln 41 (Lindenthal), Federal Republic of Germany

    Karl Herholz

  2. Universitätsklinik für Neurologie, Joseph-Stelzmann-Strasse 9, D-5000, Köln 41 (Lindenthal), Federal Republic of Germany

    Karl Herholz

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Herholz, K. Non-stationary spatial filtering and accelerated curve fitting for parametric imaging with dynamic PET. Eur J Nucl Med 14, 477–484 (1988). https://doi.org/10.1007/BF00252392

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  • DOI: https://doi.org/10.1007/BF00252392

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