Colour Deconvolution – stain unmixing in histological imaging

Gabriel Landini, Giovanni Martinelli, Filippo Piccinini

Research output: Contribution to journalArticlepeer-review

117 Downloads (Pure)

Abstract

Motivation: Microscopy images of stained cells and tissues play a central role in most biomedical experiments and routine histopathology. Storing colour histological images digitally opens the possibility to process numerically colour distribution and intensity to extract quantitative data. Among those numerical procedures is colour deconvolution, which enables decomposing an RGB image into channels representing the optical absorbance and transmittance of the dyes when their RGB representation is known. Consequently, a range of new applications become possible for morphological and histochemical segmentation, automated marker localisation and image enhancement.

Availability and implementation: Colour deconvolution is presented here in two open-source forms: a MATLAB program/function and an ImageJ plugin written in Java. Both versions run in Windows, Macintosh, and UNIX-based systems under the respective platforms. Source code and further documentation are available at: https://blog.bham.ac.uk/intellimic/g-landini-software/colour-deconvolution-2/

Supplementary information: Supplementary data are available at Bioinformatics online.
Original languageEnglish
JournalBioinformatics
Early online date30 Sep 2020
DOIs
Publication statusE-pub ahead of print - 30 Sep 2020

Fingerprint

Dive into the research topics of 'Colour Deconvolution – stain unmixing in histological imaging'. Together they form a unique fingerprint.

Cite this