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Deriving high contrast fluorescence microscopy images through low contrast noisy image stacks

Permanent link
https://hdl.handle.net/10037/23845
DOI
https://doi.org/10.1364/BOE.422747
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Date
2021-08-11
Type
Journal article
Tidsskriftartikkel
Peer reviewed

Author
Acuna Maldonado, Sebastian Andres; ROY, MAYANK; Villegas, Luis; Dubey, Vishesh Kumar; Ahluwalia, Balpreet Singh; Agarwal, Krishna
Abstract
Contrast in fluorescence microscopy images allows for the differentiation between different structures by their difference in intensities. However, factors such as point-spread function and noise may reduce it, affecting its interpretability. We identified that fluctuation of emitters in a stack of images can be exploited to achieve increased contrast when compared to the average and Richardson-Lucy deconvolution. We tested our methods on four increasingly challenging samples including tissue, in which case results were comparable to the ones obtained by structured illumination microscopy in terms of contrast.
Is part of
Acuna Maldonado, S.A. (2023). Multiple Signal Classification Algorithm: A computational microscopy tool for fluorescence microscopy. (Doctoral thesis). https://hdl.handle.net/10037/31879.
Publisher
Optical Society of America
Citation
Acuna Maldonado, ROY, Villegas, Dubey, Ahluwalia, Agarwal. Deriving high contrast fluorescence microscopy images through low contrast noisy image stacks. Biomedical Optics Express. 2021
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