Deep learning 2D and 3D optical sectioning microscopy using cross-modality Pix2Pix cGAN image translation.
Biomed Opt Express
; 12(12): 7526-7543, 2021 Dec 01.
Article
em En
| MEDLINE
| ID: mdl-35003850
ABSTRACT
Structured illumination microscopy (SIM) reconstructs optically-sectioned images of a sample from multiple spatially-patterned wide-field images, but the traditional single non-patterned wide-field images are more inexpensively obtained since they do not require generation of specialized illumination patterns. In this work, we translated wide-field fluorescence microscopy images to optically-sectioned SIM images by a Pix2Pix conditional generative adversarial network (cGAN). Our model shows the capability of both 2D cross-modality image translation from wide-field images to optical sections, and further demonstrates potential to recover 3D optically-sectioned volumes from wide-field image stacks. The utility of the model was tested on a variety of samples including fluorescent beads and fresh human tissue samples.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Biomed Opt Express
Ano de publicação:
2021
Tipo de documento:
Article