GAN-based quantitative oblique back-illumination microscopy enables computationally efficient epi-mode refractive index tomography.


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 Aug 2024
Historique:
received: 01 05 2024
revised: 09 06 2024
accepted: 10 06 2024
medline: 30 9 2024
pubmed: 30 9 2024
entrez: 30 9 2024
Statut: epublish

Résumé

Quantitative oblique back-illumination microscopy (qOBM) is a novel imaging technology that enables epi-mode 3D quantitative phase imaging and refractive index (RI) tomography of thick scattering samples. The technology uses four oblique back illumination images captured at the same focal plane and a fast 2D deconvolution reconstruction algorithm to reconstruct 2D phase cross-sections of thick samples. Alternatively, a through-focus z-stack of oblique back illumination images can be used to recover 3D RI tomograms with improved RI quantitative fidelity at the cost of a more computationally expensive reconstruction algorithm. Here, we report on a generative adversarial network (GAN) assisted approach to reconstruct 3D RI tomograms with qOBM that achieves high fidelity and greatly reduces processing time. The proposed approach achieves high-fidelity 3D RI tomography using differential phase contrast images from three adjacent z-planes. A ∼9-fold improvement in volumetric reconstruction time is achieved. We further show that this technique provides high SNR RI tomograms with high quantitative fidelity, reduces motion artifacts, and generalizes to different tissue types. This work can lead to real-time, high-fidelity RI tomographic imaging for

Identifiants

pubmed: 39346989
doi: 10.1364/BOE.528968
pii: 528968
pmc: PMC11427205
doi:

Banques de données

figshare
['10.6084/m9.figshare.26014279']

Types de publication

Journal Article

Langues

eng

Pagination

4764-4774

Informations de copyright

© 2024 Optica Publishing Group.

Déclaration de conflit d'intérêts

The authors declare no conflicts of interest.

Auteurs

Zhenmin Li (Z)

School of Electrical and Computer Engineering, Georgia Institute of Technology, USA.

Paloma Casteleiro Costa (P)

School of Electrical and Computer Engineering, Georgia Institute of Technology, USA.

Zhe Guang (Z)

Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, USA.

Caroline Filan (C)

George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, USA.

Francisco E Robles (FE)

Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, USA.

Classifications MeSH