frcoloc

Version 1.6.0.0 (11,9 KB) von Sascha D. Krauß
Colocalization of Fluorescence and Raman Microscopic Images for Training Data Collection
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Aktualisiert 10. Nov 2016

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This colocalization scheme unveils statistically significant overlapping regions by identifying correlation between fluorescence color channels and clusters from unsupervised machine learning methods like hierarchical cluster analysis (HCA) performed on Raman or CARS spectral images. The scheme works as a pre-selection to gather appropriate spectra which can be used as training data to establish a supervised classifier (e.g. Random Forest) to automatically identify subcellular compartments.
A dataset for testing can be downloaded here: http://www2.rz.rub.de:8234/imperia/md/content/pure/supplement.zip
Cite: Krauß, Sascha D., et al. "Colocalization of fluorescence and Raman microscopic images for the identification of subcellular compartments: a validation study." Analyst (2015). http://dx.doi.org/10.1039/C4AN02153C

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Sascha D. Krauß (2024). frcoloc (https://www.mathworks.com/matlabcentral/fileexchange/46608-frcoloc), MATLAB Central File Exchange. Abgerufen.

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Version Veröffentlicht Versionshinweise
1.6.0.0

Added http://dx.doi.org/10.1039/C4AN02153C
Tiny change of unnecessary code lines.
1.5.0.0

Added Citation.
1.4.0.0

Added some comments to the source code.
1.3.0.0

- New source code version, including for example different correlation coefficients.
- New name.
- New link to the test data set.
1.2.0.0

Misspelling.
1.1.0.0

Changed name of directory and improved description.
1.0.0.0