GSURE criterion for unsupervised regularized reconstruction in tomographic diffractive microscopy.
Fiche publication
Date publication
février 2022
Journal
Journal of the Optical Society of America. A, Optics, image science, and vision
Auteurs
Membres identifiés du Cancéropôle Est :
Pr HAEBERLE Olivier
Tous les auteurs :
Denneulin L, Momey F, Brault D, Debailleul M, Taddese AM, Verrier N, Haeberlé O
Lien Pubmed
Résumé
We propose an unsupervised regularized inversion method for reconstruction of the 3D refractive index map of a sample in tomographic diffractive microscopy. It is based on the minimization of the generalized Stein's unbiased risk estimator (GSURE) to automatically estimate optimal values for the hyperparameters of one or several regularization terms (sparsity, edge-preserving smoothness, total variation). We evaluate the performance of our approach on simulated and experimental limited-view data. Our results show that GSURE is an efficient criterion to find suitable regularization weights, which is a critical task, particularly in the context of reducing the amount of required data to allow faster yet efficient acquisitions and reconstructions.
Référence
J Opt Soc Am A Opt Image Sci Vis. 2022 Feb 1;39(2):A52-A61