RADIAL NOISE FILTERING IN POSITRON EMISSION TOMOGRAPHY

The quality of the images from positron emission tomography (PET) is regularly degraded by radial streak artifacts. In many cases this is attributed to data undersampling and the inexactitude of the models used in the image reconstruction. Because this noise cannot be easily isolated in either spatial or spectral domains, classical noise filtering techniques have proven inadequate. As an alternative, we propose a new filtering method, which is implemented as follows. The image is converted from the original rectangular x-y coordinate system into a polar ρ-θ coordinate system. This causes the radial noise to map into well-defined horizontal streaks. After a polar transformation, radial noise is mapped around one of the axes of the Fourier spectrum in the corresponding ω-m space. We have modeled radial noise using both rectangular and polar representations and have shown both analytically and through computer simulation that these streaks exhibit consistent mapping patterns. A class of filters is designed accordingly and applied to the image.