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|Title:||A knowledge-based image smoothing technique for dynamic PET studies|
|Keywords:||Knowledge based systems|
Medical image processing
Positron emission tomography
|Source:||2000 IEEE Nuclear Science Symposium conference record : October 15-20, 2000, Lyon, France, v. 3, p. 18/114 - 18/117 How to cite?|
|Abstract:||Many techniques have been proposed to reduce image noise in dynamic positron emission tomography (PET) imaging. However, these smoothing methods are usually based on the spatial domain and local statistical properties. Smoothing algorithms specifically designed for dynamic image data have not previously been investigated in detail. We present a knowledge-based smoothing technique that aims to diminish the noise and improve the quality of the dynamic images. By taking advantage of domain specific physiological kinetic knowledge, this technique can provide dynamic images with high noise reduction while preserving edges and subtle details.|
|Rights:||© 2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
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|Appears in Collections:||Conference Paper|
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