Muon tomographic visualization techniques try to reconstruct a 3D image as close as possible to the real localization of the objects being probed. Statistical algorithms under test for the reconstruction of muon tomographic images in the Muon Portal Project are discussed here. Autocorrelation analysis and clustering algorithms have been employed within the context of methods based on the Point Of Closest Approach (POCA) reconstruction tool. An iterative method based on the log-likelihood approach was also implemented. Relative merits of all such methods are discussed, with reference to full GEANT4 simulations of different scenarios, incorporating medium and high-Z objects inside a container. (C) 2013 Elsevier B.V. All rights reserved.
Muon tomography imaging algorithms for nuclear threat detection inside large volume containers with the Muon Portal detector
LA ROCCA, PAOLA;PETTA, Catia Maria Annunziata;RIGGI, Francesco;Vitello F.
2013-01-01
Abstract
Muon tomographic visualization techniques try to reconstruct a 3D image as close as possible to the real localization of the objects being probed. Statistical algorithms under test for the reconstruction of muon tomographic images in the Muon Portal Project are discussed here. Autocorrelation analysis and clustering algorithms have been employed within the context of methods based on the Point Of Closest Approach (POCA) reconstruction tool. An iterative method based on the log-likelihood approach was also implemented. Relative merits of all such methods are discussed, with reference to full GEANT4 simulations of different scenarios, incorporating medium and high-Z objects inside a container. (C) 2013 Elsevier B.V. All rights reserved.File | Dimensione | Formato | |
---|---|---|---|
Muon tomography imaging algorithms for nuclear threat detection inside large volume containers with the Muon Portal detector.pdf
solo gestori archivio
Tipologia:
Versione Editoriale (PDF)
Licenza:
NON PUBBLICO - Accesso privato/ristretto
Dimensione
4.59 MB
Formato
Adobe PDF
|
4.59 MB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.