Over the last years many statistical models have been proposed to restore tomographical images. However, their use in medical environment has been limited due to several factors. ...
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...
This paper deals with denoising of density images with bad Poisson statistics (low count rates), where the reconstruction of the major structures seems the only reasonable task. Ob...
This paper presents a method to take advantage of artificial evolution in positron emission tomography reconstruction. This imaging technique produces datasets that correspond to t...
Franck Patrick Vidal, Delphine Lazaro-Ponthus, Sam...
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...