A nonlinear mapping approach to stain normalization in digital histopathology images using image-specific color deconvolution
- Submitting institution
-
The University of Leeds
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- UOA11-4623
- Type
- D - Journal article
- DOI
-
10.1109/TBME.2014.2303294
- Title of journal
- IEEE Transactions on Biomedical Engineering
- Article number
- -
- First page
- 1729
- Volume
- 61
- Issue
- 6
- ISSN
- 0018-9294
- Open access status
- Out of scope for open access requirements
- Month of publication
- January
- Year of publication
- 2014
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
3
- Research group(s)
-
C - BMH (Applied Computing in Biology, Medicine and Health)
- Citation count
- 210
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- The standard benchmark/reference on colour normalisation(CN) in digital pathology. Presents first non-linear CN method and shows superiority to competing methods. CN is important in digital pathology for standardisation of images between labs and for analysis to work in the real-world, and since microscopes work with subtractive rather than additive colour, and *multiple* stains vary separately in their effect on each frequency. Resulted in the widely used Warwick CN toolbox(more than 3000 downloads)(https://warwick.ac.uk/fac/sci/dcs/research/tia/software/sntoolbox/) and is part of Colour Analysis add-on from Leeds spin-out HeteroGenius Ltd(Derek.Magee@heterogenius.co.uk) -- http://ww.w.medicalimagemanager.com/features/colour/index.html, with sales across UK, Europe and Asia(Japan/Korea). More than 8600 full-text views.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
