Studente Guazzo, Alessandro
Facoltà/Dipartimento Scuola di Ingegneria
???if.relation.course.label??? BIOINGEGNERIA
???if.relation.academicyear.label??? 2020-03-09
Titolo originale Deep Learning for PET Imaging: from Denoising to Learned Primal-Dual Reconstruction
Abstract One of the main issues of PET imaging is the high level of noise that characterizes the reconstructed image. During this project we implemented several algorithms with the aim of improving the reconstruction of PET images exploiting the power of Neural Networks. We developed a simple Denoiser, then two Neural Network based iterative reconstruction algorithms and finally, we used the most promising approach to reconstruct images from data acquired with the KTH MTH microCT - miniPET.
???if.keyword.label??? deep learning, PET imaging, denoising, reconstruction, neural networks
???if.supervisor.label??? Bertoldo, Alessandra
Correlatore Colarieti-Tosti, Massimiliano
Appare nelle tipologie: Lauree magistrali
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12608/20967