4.7 Article

Colour deconvolution: stain unmixing in histological imaging

Journal

BIOINFORMATICS
Volume 37, Issue 10, Pages 1485-1487

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btaa847

Keywords

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Funding

  1. Engineering & Physical Sciences Research Council (EPSRC), UK [EP/M023869/1]
  2. EPSRC [EP/M023869/1] Funding Source: UKRI

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Storing color histological images digitally allows for processing and extracting quantitative data through methods such as color deconvolution, enabling new applications like morphological and histochemical segmentation, automated marker localization, and image enhancement.
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 are colour deconvolution, which enable 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 localization and image enhancement.

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