Ordered subsets convex algorithm for 3D terahertz transmission tomography

Abstract : We investigate in this paper a new reconstruction method in order to perform 3D Terahertz (THz) tomography using a continuous wave acquisition setup in transmission mode. This method is based on the Maximum Likelihood for TRansmission tomography (ML-TR) first developed for X-ray imaging. We optimize the Ordered Subsets Convex (OSC) implementation of the ML-TR by including the Gaussian propagation model of THz waves and take into account the intensity distributions of both blank calibration scan and dark-field measured on THz detectors. THz ML-TR reconstruction quality and accuracy are discussed and compared to other tomographic reconstructions.
Type de document :
Article dans une revue
Optics Express, Optical Society of America, 2014, 22 (19), pp.23299-23309. 〈10.1364/OE.22.023299〉
Liste complète des métadonnées

Littérature citée [27 références]  Voir  Masquer  Télécharger

https://hal.archives-ouvertes.fr/hal-01066999
Contributeur : Bernadette Bergeret <>
Soumis le : lundi 23 mars 2015 - 11:30:37
Dernière modification le : mardi 24 mars 2015 - 01:04:42
Document(s) archivé(s) le : mercredi 9 novembre 2016 - 09:40:33

Fichier

RecurOE2014_PostPrint.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Citation

Benoît Recur, Hugo Balacey, Joyce Bou Sleiman, Jean-Baptiste Perraud, Jean-Paul Guillet, et al.. Ordered subsets convex algorithm for 3D terahertz transmission tomography. Optics Express, Optical Society of America, 2014, 22 (19), pp.23299-23309. 〈10.1364/OE.22.023299〉. 〈hal-01066999〉

Partager

Métriques

Consultations de
la notice

198

Téléchargements du document

96