Studying the effect of digital stain separation of histopathology images on image search performance

Alison K. Cheeseman, Hamid R. Tizhoosh, Edward R. Vrscay

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Due to recent advances in technology, digitized histopathology images are now widely available for both clinical and research purposes. Accordingly, research into computerized image analysis algorithms for digital histopathology images has been progressing rapidly. In this work, we focus on image retrieval for digital histopathology images. Image retrieval algorithms can be used to find similar images and can assist pathologists in making quick and accurate diagnoses. Histopathology images are typically stained with dyes to highlight features of the tissue, and as such, an image analysis algorithm for histopathology should be able to process colour images and determine relevant information from the stain colours present. In this study, we are interested in the effect that stain separation into their individual stain components has on image search performance. To this end, we implement a basic k-nearest neighbours (kNN) search algorithm on histopathology images from two publicly available data sets (IDC and BreakHis) which are: a) converted to greyscale, b) digitally stain-separated and c) the original RGB colour images. The results of this study show that using H&E separated images yields search accuracies within one or two percent of those obtained with original RGB images, and that superior performance is observed using the H&E images in most scenarios we tested.

Original languageEnglish (US)
Title of host publicationImage Analysis and Recognition - 17th International Conference, ICIAR 2020, Proceedings
EditorsAurélio Campilho, Fakhri Karray, Zhou Wang
Number of pages12
ISBN (Print)9783030505158
StatePublished - 2020
Event17th International Conference on Image Analysis and Recognition, ICIAR 2020 - Póvoa de Varzim, Portugal
Duration: Jun 24 2020Jun 26 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12132 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference17th International Conference on Image Analysis and Recognition, ICIAR 2020
CityPóvoa de Varzim


  • Digital histopathology
  • Digital image retrieval and classification
  • Digital stain separation
  • Encoded Local Projections (ELP)

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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