Deep learning-based fusion of widefield diffuse optical tomography and micro-CT structural priors for accurate 3D reconstructions.
Journal
Biomedical optics express
ISSN: 2156-7085
Titre abrégé: Biomed Opt Express
Pays: United States
ID NLM: 101540630
Informations de publication
Date de publication:
01 Mar 2023
01 Mar 2023
Historique:
received:
04
11
2022
revised:
10
01
2023
accepted:
24
01
2023
entrez:
23
3
2023
pubmed:
24
3
2023
medline:
24
3
2023
Statut:
epublish
Résumé
Widefield illumination and detection strategies leveraging structured light have enabled fast and robust probing of tissue properties over large surface areas and volumes. However, when applied to diffuse optical tomography (DOT) applications, they still require a time-consuming and expert-centric solving of an ill-posed inverse problem. Deep learning (DL) models have been recently proposed to facilitate this challenging step. Herein, we expand on a previously reported deep neural network (DNN) -based architecture (modified AUTOMAP - ModAM) for accurate and fast reconstructions of the absorption coefficient in 3D DOT based on a structured light illumination and detection scheme. Furthermore, we evaluate the improved performances when incorporating a micro-CT structural prior in the DNN-based workflow, named Z-AUTOMAP. This Z-AUTOMAP significantly improves the widefield imaging process's spatial resolution, especially in the transverse direction. The reported DL-based strategies are validated both
Identifiants
pubmed: 36950248
doi: 10.1364/BOE.480091
pii: 480091
pmc: PMC10026582
doi:
Types de publication
Journal Article
Langues
eng
Pagination
1041-1053Subventions
Organisme : NCI NIH HHS
ID : R01 CA207725
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA237267
Pays : United States
Organisme : NCI NIH HHS
ID : R01 CA250636
Pays : United States
Informations de copyright
© 2023 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.
Déclaration de conflit d'intérêts
The authors declare no conflicts of interest.
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