Colocalization of fluorescence and Raman microscopic images for the identification of subcellular compartments: a validation study. Issue 7 (13th February 2015)
- Record Type:
- Journal Article
- Title:
- Colocalization of fluorescence and Raman microscopic images for the identification of subcellular compartments: a validation study. Issue 7 (13th February 2015)
- Main Title:
- Colocalization of fluorescence and Raman microscopic images for the identification of subcellular compartments: a validation study
- Authors:
- Krauß, Sascha D.
Petersen, Dennis
Niedieker, Daniel
Fricke, Inka
Freier, Erik
El-Mashtoly, Samir F.
Gerwert, Klaus
Mosig, Axel - Abstract:
- Abstract : This paper introduces algorithms for identifying overlapping observations between Raman and fluorescence microscopic images of one and the same sample. Abstract : A major promise of Raman microscopy is the label-free detailed recognition of cellular and subcellular structures. To this end, identifying colocalization patterns between Raman spectral images and fluorescence microscopic images is a key step to annotate subcellular components in Raman spectroscopic images. While existing approaches to resolve subcellular structures are based on fluorescence labeling, we propose a combination of a colocalization scheme with subsequent training of a supervised classifier that allows label-free resolution of cellular compartments. Our colocalization scheme unveils statistically significant overlapping regions by identifying correlation between the fluorescence color channels and clusters from unsupervised machine learning methods like hierarchical cluster analysis. The colocalization scheme is used as a pre-selection to gather appropriate spectra as training data. These spectra are used in the second part as training data to establish a supervised random forest classifier to automatically identify lipid droplets and nucleus. We validate our approach by examining Raman spectral images overlaid with fluorescence labelings of different cellular compartments, indicating that specific components may indeed be identified label-free in the spectral image. A Matlab implementationAbstract : This paper introduces algorithms for identifying overlapping observations between Raman and fluorescence microscopic images of one and the same sample. Abstract : A major promise of Raman microscopy is the label-free detailed recognition of cellular and subcellular structures. To this end, identifying colocalization patterns between Raman spectral images and fluorescence microscopic images is a key step to annotate subcellular components in Raman spectroscopic images. While existing approaches to resolve subcellular structures are based on fluorescence labeling, we propose a combination of a colocalization scheme with subsequent training of a supervised classifier that allows label-free resolution of cellular compartments. Our colocalization scheme unveils statistically significant overlapping regions by identifying correlation between the fluorescence color channels and clusters from unsupervised machine learning methods like hierarchical cluster analysis. The colocalization scheme is used as a pre-selection to gather appropriate spectra as training data. These spectra are used in the second part as training data to establish a supervised random forest classifier to automatically identify lipid droplets and nucleus. We validate our approach by examining Raman spectral images overlaid with fluorescence labelings of different cellular compartments, indicating that specific components may indeed be identified label-free in the spectral image. A Matlab implementation of our colocalization software is available at Web:http://www.mathworks.de/matlabcentral/fileexchange/46608-frcoloc . … (more)
- Is Part Of:
- Analyst. Volume 140:Issue 7(2015)
- Journal:
- Analyst
- Issue:
- Volume 140:Issue 7(2015)
- Issue Display:
- Volume 140, Issue 7 (2015)
- Year:
- 2015
- Volume:
- 140
- Issue:
- 7
- Issue Sort Value:
- 2015-0140-0007-0000
- Page Start:
- 2360
- Page End:
- 2368
- Publication Date:
- 2015-02-13
- Subjects:
- Chemistry, Analytic -- Periodicals
543 - Journal URLs:
- http://pubs.rsc.org/en/journals/journalissues/an?e=1#!issueid=an139020&type=current&issnprint=0003-2654 ↗
http://www.rsc.org/ ↗ - DOI:
- 10.1039/c4an02153c ↗
- Languages:
- English
- ISSNs:
- 0003-2654
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 0893.000000
British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 4875.xml