Computational nanosensing from defocus in single particle interferometric reflectance microscopy
Files
Accepted manuscript
Date
2020-12-01
Authors
Yurdakul, Celalettin
Ünlü, M. Selim
Version
Accepted manuscript
Embargo Date
2021-12-01
OA Version
Citation
Celalettin Yurdakul, M Selim Ünlü. 2020. "Computational nanosensing from defocus in single particle interferometric reflectance microscopy." Opt Lett, Volume 45, Issue 23, pp. 6546 - 6549. https://doi.org/10.1364/OL.409458
Abstract
Single particle interferometric reflectance (SPIR) microscopy has been studied as a powerful imaging platform for label-free and highly sensitive biological nanoparticle detection and characterization. SPIR's interferometric nature yields a unique 3D defocus intensity profile of the nanoparticles over a large field of view. Here, we utilize this defocus information to recover high signal-to-noise ratio nanoparticle images with a computationally and memory efficient reconstruction framework. Our direct inversion approach recovers this image from a 3D defocus intensity stack using the vectorial-optics-based forward model developed for sub-diffraction-limited dielectric nanoparticles captured on a layered substrate. We demonstrate proof-of-concept experiments on silica beads with a 50 nm nominal diameter.
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© 2020 Optical Society of America. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modifications of the content of this paper are prohibited.