Abstract
The presence of Nuclear Medicine as a medical imaging modality is one of the main procedures utilized nowadays in medical centers, and the great advantage of that procedure is its capacity to analyze the metabolic behavior of the patient, resulting in early diagnoses. This project aims to investigate the dynamic and the metabolic quantification of dynamic 3D medical images of the PET/CT modality. However, the quantification in Nuclear Medicine is known to be complicated by many factors, such as degradations due to attenuation, scattering, reconstruction algorithms and models. In this context, the goal is to improve the accuracy and the precision of quantification in PET/CT images by means of realistic and well-controlled processes. For this purpose, we propose the development of a framework, which consists in a set of consecutively interlinked steps that are initiated with the simulation of 3D dynamic anthropomorphic phantoms. These phantoms, subsequently, will be used to generate the realistic PET/CT projections by applying the GATE platform (with Monte Carlo simulation). Then a pre-processing phase will be applied to reduce Poisson noise, characteristic of this type of images, by using the Anscombe/Lee filter. With improved projections after filtration, 3D image reconstruction will be executed, followed by filtering and segmentation steps (based on Fuzzy Connectedness theory). After defining the region of interest (ROI), input activity and output response curves, are required for the compartment analysis in order to obtain the Metabolic Quantification of the selected organ or structure. Finally, evaluation procedures will be utilized to verify the efficiency and precision level of the application. Analogously, to certify the validity of our process, real images provided from the Center of Nuclear Medicine of the HC and the Heart Institute will be analysed.
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