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An alternative reference space for H&E color normalization

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  • Mark D Zarella
  • Chan Yeoh
  • David E Breen
  • Fernando U Garcia

Abstract

Digital imaging of H&E stained slides has enabled the application of image processing to support pathology workflows. Potential applications include computer-aided diagnostics, advanced quantification tools, and innovative visualization platforms. However, the intrinsic variability of biological tissue and the vast differences in tissue preparation protocols often lead to significant image variability that can hamper the effectiveness of these computational tools. We developed an alternative representation for H&E images that operates within a space that is more amenable to many of these image processing tools. The algorithm to derive this representation operates by exploiting the correlation between color and the spatial properties of the biological structures present in most H&E images. In this way, images are transformed into a structure-centric space in which images are segregated into tissue structure channels. We demonstrate that this framework can be extended to achieve color normalization, effectively reducing inter-slide variability.

Suggested Citation

  • Mark D Zarella & Chan Yeoh & David E Breen & Fernando U Garcia, 2017. "An alternative reference space for H&E color normalization," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-14, March.
    • Handle: RePEc:plo:pone00:0174489
    DOI: 10.1371/journal.pone.0174489
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    1. Irshad, Humayun & Jalali, Sepehr & Roux, Ludovic & Racoceanu, Daniel & Joo-Hwee, Lim & Naour, Gilles Le & Capron, Frédérique, "undated". "Automated Mitosis Detection Using Texture, SIFT Features and HMAX Biologically Inspired Approach," Working Paper 221761, Harvard University OpenScholar.
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