In this paper we describe a neural network-based method aimed at automatically calibrating the detector module contained in a scanner for a highresolution positron emission tomogra...
Beatrice Lazzerini, Francesco Marcelloni, Giovanni...
A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
With continuing improvements in spatial resolution of positron emission tomography (PET) scanners, small patient movements during PET imaging become a significant source of resolut...
We present a fully four-dimensional, globally convergent, incremental gradient algorithm to estimate the continuous-time tracer density from list mode positron emission tomography...
Abstract. This paper presents an evolutionary approach for image reconstruction in positron emission tomography (PET). Our reconstruction method is based on a cooperative coevoluti...
Franck Patrick Vidal, Jean Louchet, Jean-Marie Roc...