Deriving high contrast fluorescence microscopy images through low contrast noisy image stacks
Permanent lenke
https://hdl.handle.net/10037/23845Dato
2021-08-11Type
Journal articleTidsskriftartikkel
Peer reviewed
Forfatter
Acuna Maldonado, Sebastian Andres; ROY, MAYANK; Villegas, Luis; Dubey, Vishesh Kumar; Ahluwalia, Balpreet Singh; Agarwal, KrishnaSammendrag
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.
Er en del av
Acuna Maldonado, S.A. (2023). Multiple Signal Classification Algorithm: A computational microscopy tool for fluorescence microscopy. (Doctoral thesis). https://hdl.handle.net/10037/31879.Forlag
Optical Society of AmericaSitering
Acuna Maldonado, ROY, Villegas, Dubey, Ahluwalia, Agarwal. Deriving high contrast fluorescence microscopy images through low contrast noisy image stacks. Biomedical Optics Express. 2021Metadata
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Copyright 2021 The Author(s)