Deep learning-assisted low-cost autofluorescence microscopy for rapid slide-free imaging with virtual histological staining.
Biomed Opt Express
; 15(4): 2187-2201, 2024 Apr 01.
Article
en En
| MEDLINE
| ID: mdl-38633074
ABSTRACT
Slide-free imaging techniques have shown great promise in improving the histological workflow. For example, computational high-throughput autofluorescence microscopy by pattern illumination (CHAMP) has achieved high resolution with a long depth of field, which, however, requires a costly ultraviolet laser. Here, simply using a low-cost light-emitting diode (LED), we propose a deep learning-assisted framework of enhanced widefield microscopy, termed EW-LED, to generate results similar to CHAMP (the learning target). Comparing EW-LED and CHAMP, EW-LED reduces the cost by 85×, shortening the image acquisition time and computation time by 36× and 17×, respectively. This framework can be applied to other imaging modalities, enhancing widefield images for better virtual histology.
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1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Biomed Opt Express
Año:
2024
Tipo del documento:
Article
País de afiliación:
China
Pais de publicación:
Estados Unidos