Structure-preserved color normalization for histological images

Abhishek Vahadane, Tingying Peng, Shadi Albarqouni, Maximilian Baust, Katja Steiger, Anna Melissa Schlitter, Amit Sethi, Irene Esposito, Nassir Navab

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

78 Scopus citations


Automated image processing and quantification are increasingly gaining attention in the field of digital pathology. However, a common problem that encumbers computerized analysis is the color variation in histology, due to the use of different microscopes/scanners, or inconsistencies in tissue preparation. In this paper, we present a novel color normalization technique to bring a histological image (source image) into a different color appearance of a second image (target image), which therefore standardizes the color representation of both images. In particular, by incorporating biological stain-sparse regularized stain separation, our color normalization technique preserves the structural information of the source image after color normalization, which is very important for subsequent image analysis. Both qualitative and quantitative validation demonstrates the superior performance of our stain separation and color normalization techniques.

Original languageEnglish
Title of host publication2015 IEEE 12th International Symposium on Biomedical Imaging, ISBI 2015
PublisherIEEE Computer Society
Number of pages4
ISBN (Electronic)9781479923748
StatePublished - 21 Jul 2015
Event12th IEEE International Symposium on Biomedical Imaging, ISBI 2015 - Brooklyn, United States
Duration: 16 Apr 201519 Apr 2015

Publication series

NameProceedings - International Symposium on Biomedical Imaging
ISSN (Print)1945-7928
ISSN (Electronic)1945-8452


Conference12th IEEE International Symposium on Biomedical Imaging, ISBI 2015
Country/TerritoryUnited States


  • Histopathology image
  • color normalization
  • non-negative matrix factorization
  • stain separation


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