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BMC Bioinformatics. 2015 Oct 26;16:344. doi: 10.1186/s12859-015-0782-y.

CytoSpectre: a tool for spectral analysis of oriented structures on cellular and subcellular levels.

Author information

1
Department of Automation Science and Engineering, Tampere University of Technology, BioMediTech, Tampere, Finland. kimmo.kartasalo@uta.fi.
2
University of Tampere, BioMediTech, Tampere, Finland. risto-pekka.polonen@staff.uta.fi.
3
School of Medicine, University of Tampere, Tampere, Finland. risto-pekka.polonen@staff.uta.fi.
4
University of Tampere, BioMediTech, Tampere, Finland. marisa.ojala@uta.fi.
5
School of Information Sciences, University of Tampere, Tampere, Finland. jyrki.rasku@uta.fi.
6
Department of Automation Science and Engineering, Tampere University of Technology, BioMediTech, Tampere, Finland. jukka.lekkala@tut.fi.
7
University of Tampere, BioMediTech, Tampere, Finland. katriina.aalto-setala@uta.fi.
8
School of Medicine, University of Tampere, Tampere, Finland. katriina.aalto-setala@uta.fi.
9
Heart Hospital, Tampere University Hospital, Tampere, Finland. katriina.aalto-setala@uta.fi.
10
Department of Automation Science and Engineering, Tampere University of Technology, BioMediTech, Tampere, Finland. pasi.kallio@tut.fi.

Abstract

BACKGROUND:

Orientation and the degree of isotropy are important in many biological systems such as the sarcomeres of cardiomyocytes and other fibrillar structures of the cytoskeleton. Image based analysis of such structures is often limited to qualitative evaluation by human experts, hampering the throughput, repeatability and reliability of the analyses. Software tools are not readily available for this purpose and the existing methods typically rely at least partly on manual operation.

RESULTS:

We developed CytoSpectre, an automated tool based on spectral analysis, allowing the quantification of orientation and also size distributions of structures in microscopy images. CytoSpectre utilizes the Fourier transform to estimate the power spectrum of an image and based on the spectrum, computes parameter values describing, among others, the mean orientation, isotropy and size of target structures. The analysis can be further tuned to focus on targets of particular size at cellular or subcellular scales. The software can be operated via a graphical user interface without any programming expertise. We analyzed the performance of CytoSpectre by extensive simulations using artificial images, by benchmarking against FibrilTool and by comparisons with manual measurements performed for real images by a panel of human experts. The software was found to be tolerant against noise and blurring and superior to FibrilTool when analyzing realistic targets with degraded image quality. The analysis of real images indicated general good agreement between computational and manual results while also revealing notable expert-to-expert variation. Moreover, the experiment showed that CytoSpectre can handle images obtained of different cell types using different microscopy techniques. Finally, we studied the effect of mechanical stretching on cardiomyocytes to demonstrate the software in an actual experiment and observed changes in cellular orientation in response to stretching.

CONCLUSIONS:

CytoSpectre, a versatile, easy-to-use software tool for spectral analysis of microscopy images was developed. The tool is compatible with most 2D images and can be used to analyze targets at different scales. We expect the tool to be useful in diverse applications dealing with structures whose orientation and size distributions are of interest. While designed for the biological field, the software could also be useful in non-biological applications.

PMID:
26503371
PMCID:
PMC4624586
DOI:
10.1186/s12859-015-0782-y
[Indexed for MEDLINE]
Free PMC Article

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