Digital staining through the application of deep neural networks to multi-modal multi-photon microscopy.
Biomed Opt Express
; 10(3): 1339-1350, 2019 Mar 01.
Article
en En
| MEDLINE
| ID: mdl-30891350
ABSTRACT
Deep neural networks have been used to map multi-modal, multi-photon microscopy measurements of a label-free tissue sample to its corresponding histologically stained brightfield microscope colour image. It is shown that the extra structural and functional contrasts provided by using two source modes, namely two-photon excitation microscopy and fluorescence lifetime imaging, result in a more faithful reconstruction of the target haematoxylin and eosin stained mode. This modal mapping procedure can aid histopathologists, since it provides access to unobserved imaging modalities, and translates the high-dimensional numerical data generated by multi-modal, multi-photon microscopy into traditionally accepted visual forms. Furthermore, by combining the strengths of traditional chemical staining and modern multi-photon microscopy techniques, modal mapping enables label-free, non-invasive studies of in vivo tissue samples or intravital microscopic imaging inside living animals. The results show that modal co-registration and the inclusion of spatial variations increase the visual accuracy of the mapped results.
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1
Colección:
01-internacional
Base de datos:
MEDLINE
Idioma:
En
Revista:
Biomed Opt Express
Año:
2019
Tipo del documento:
Article
País de afiliación:
Suiza