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Spatially-varying microscope calibration from unstructured sparse inputs

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Abstract

We propose a method based on blind deconvolution to calibrate the spatially-varying point spread functions of a coded-aperture microscope system. From easy-to- acquire measurements of unstructured fluorescent beads, we recover a spatially-varying forward model that outperforms prior approaches.

© 2020 The Author(s)

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More Like This
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Amit Kohli, Anastasios Angelopoulos, Sixian You, and Laura Waller
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Kyrollos Yanny, Nick Antipa, William Liberti, Sam Dehaeck, Kristina Monakhova, Fanglin Linda Liu, Konlin Shen, Ren Ng, and Laura Waller
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