Compact Linnik-type hyperspectral quantitative phase microscope for advanced classification of cellular components.

Autor: Joshi H; Bio-photonics and Green-photonics Laboratory, Department of Physics, Indian Institute of Technology Delhi, New Delhi, India., Singh BP; Bio-photonics and Green-photonics Laboratory, Department of Physics, Indian Institute of Technology Delhi, New Delhi, India., Butola A; Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway., Surya V; Department of Oral Pathology and Microbiology, Center for Dental Education & Research, All India Institute of Medical Sciences (AIIMS), New Delhi, India., Mishra D; Department of Oral Pathology and Microbiology, Center for Dental Education & Research, All India Institute of Medical Sciences (AIIMS), New Delhi, India., Agarwal K; Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway., Mehta DS; Bio-photonics and Green-photonics Laboratory, Department of Physics, Indian Institute of Technology Delhi, New Delhi, India.
Jazyk: angličtina
Zdroj: Journal of biophotonics [J Biophotonics] 2024 Aug; Vol. 17 (8), pp. e202400088. Date of Electronic Publication: 2024 Jun 20.
DOI: 10.1002/jbio.202400088
Abstrakt: Hyperspectral quantitative phase microscopy (HS-QPM) involves the acquisition of phase images across narrow spectral bands, which enables wavelength-dependent study of different biological samples. In the present work, a compact Linnik-type HS-QPM system is developed to reduce the instability and complexity associated with conventional HS-QPM techniques. The use of a single objective lens for both reference and sample arms makes the setup compact. The capabilities of the system are demonstrated by evaluating the HS phase map of both industrial and biological specimens. Phase maps of exfoliated cheek cells at different wavelengths are stacked to form a HS phase cube, adding spectral dimensionality to spatial phase distribution. Analysis of wavelength response of different cellular components are performed using principal component analysis to identify dominant spectral features present in the HS phase dataset. Findings of the study emphasize on the efficiency and effectiveness of HS-QPM for advancing cellular characterization in biomedical research and clinical applications.
(© 2024 Wiley‐VCH GmbH.)
Databáze: MEDLINE
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