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Noise Removal with Maintained Spatial Resolution in Raman Images of Cells Exposed to Submicron Polystyrene Particles
Swedish Def Res Agcy, FOI, Cementvagen 20, SE-90182 Umea, Sweden..
Swedish Def Res Agcy, FOI, Cementvagen 20, SE-90182 Umea, Sweden..
Swedish Def Res Agcy, FOI, Cementvagen 20, SE-90182 Umea, Sweden..
Swedish Univ Agr Sci, Dept Forest Biomat & Technol, SE-90183 Umea, Sweden..
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2016 (English)In: NANOMATERIALS, ISSN 2079-4991, Vol. 6, no 5, UNSP 83Article in journal (Refereed) PublishedText
Abstract [en]

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.

Place, publisher, year, edition, pages
2016. Vol. 6, no 5, UNSP 83
Keyword [en]
Raman spectroscopy, Raman imaging, super-resolution, particles, cells, Tikhonov regularization
National Category
Radiology, Nuclear Medicine and Medical Imaging Engineering and Technology
URN: urn:nbn:se:uu:diva-299922DOI: 10.3390/nano6050083ISI: 000378805500003OAI: oai:DiVA.org:uu-299922DiVA: diva2:950343
Available from: 2016-07-29 Created: 2016-07-29 Last updated: 2016-08-19Bibliographically approved

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