Improving Positron Emission Tomography with Guided Filtering

Abstract

Positron emission tomography (PET) is a nuclear medicine imaging technique that is used to observe tissue metabolism by reconstructing the spatial distribution of the injected radioactive tracer. Due to constraints on the time and the radiation dose of the examination as well as limited scanner sensitivity, PET images usually suffer from a high level of noise. This paper focuses on the application of the guided filter for PET image denoising. After proposing several different guidance images, guided filter variants are compared with the median, the Gaussian and the bilateral filter in terms of image quality and speed. For dynamic PET reconstructions, a new approach, the parametric filtering is conceived, in which filtering is performed on the parameters of the kinetic model describing the radiotracer concentration. Finally, an efficient, guided-filter-based partial volume correction (PVC) method is proposed to restore accurate activity values that are blurred due to the partial volume effect.