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

Ahlinder, Linnea (author)
Swedish Def Res Agcy, FOI, Cementvagen 20, SE-90182 Umea, Sweden.
Lindstrom, Susanne Wiklund (author)
Swedish Def Res Agcy, FOI, Cementvagen 20, SE-90182 Umea, Sweden.
Lejon, Christian (author)
Swedish Def Res Agcy, FOI, Cementvagen 20, SE-90182 Umea, Sweden.
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Geladi, Paul (author)
Swedish University of Agricultural Sciences,Sveriges lantbruksuniversitet,Skogens biomaterial och teknologi,Department of Forest Biomaterials and Technology,Swedish Univ Agr Sci, Dept Forest Biomat & Technol, SE-90183 Umea, Sweden.
Österlund, Lars (author)
Uppsala universitet,Fasta tillståndets fysik
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Swedish Def Res Agcy, FOI, Cementvagen 20, SE-90182 Umea, Sweden Skogens biomaterial och teknologi (creator_code:org_t)
 
2016-04-29
2016
English.
In: Nanomaterials. - : MDPI AG. - 2079-4991. ; 6:5
  • Journal article (peer-reviewed)
Abstract Subject headings
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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.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)
NATURVETENSKAP  -- Kemi -- Materialkemi (hsv//swe)
NATURAL SCIENCES  -- Chemical Sciences -- Materials Chemistry (hsv//eng)

Keyword

Raman spectroscopy
Raman imaging
super-resolution
particles
cells
Tikhonov regularization

Publication and Content Type

ref (subject category)
art (subject category)

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