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Nanomaterials 2016, 6(5), 83;

Noise Removal with Maintained Spatial Resolution in Raman Images of Cells Exposed to Submicron Polystyrene Particles

Swedish Defence Research Agency, FOI, Cementvägen 20, SE-901 82 Umeå, Sweden
Department of Forest Biomaterials and Technology, Swedish University of Agricultural Sciences, SE-901 83 Umeå, Sweden
Department of Engineering Sciences, The Ångström Laboratory, Uppsala University, P.O. Box 534, SE-751 21 Uppsala, Sweden
Authors to whom correspondence should be addressed.
Academic Editor: Yurii Gun’ko
Received: 5 February 2016 / Revised: 21 April 2016 / Accepted: 26 April 2016 / Published: 29 April 2016
(This article belongs to the Special Issue Nanoparticles in Bioimaging)
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The biodistribution of 300 nm polystyrene particles in A549 lung epithelial cells has been studied with confocal Raman spectroscopy. This is a label-free method in which particles and cells can be imaged without using dyes or fluorescent labels. The main drawback with Raman imaging is the comparatively low spatial resolution, which is aggravated in heterogeneous systems such as biological samples, which in addition often require long measurement times because of their weak Raman signal. Long measurement times may however induce laser-induced damage. In this study we use a super-resolution algorithm with Tikhonov regularization, intended to improve the image quality without demanding an increased number of collected pixels. Images of cells exposed to polystyrene particles have been acquired with two different step lengths, i.e., the distance between pixels, and compared to each other and to corresponding images treated with the super-resolution algorithm. It is shown that the resolution after application of super-resolution algorithms is not significantly improved compared to the theoretical limit for optical microscopy. However, to reduce noise and artefacts in the hyperspectral Raman images while maintaining the spatial resolution, we show that it is advantageous to use short mapping step lengths and super-resolution algorithms with appropriate regularization. The proposed methodology should be generally applicable for Raman imaging of biological samples and other photo-sensitive samples. View Full-Text
Keywords: Raman spectroscopy; Raman imaging; super-resolution; particles; cells; Tikhonov regularization Raman spectroscopy; Raman imaging; super-resolution; particles; cells; Tikhonov regularization

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Ahlinder, L.; Wiklund Lindström, S.; Lejon, C.; Geladi, P.; Österlund, L. Noise Removal with Maintained Spatial Resolution in Raman Images of Cells Exposed to Submicron Polystyrene Particles. Nanomaterials 2016, 6, 83.

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