Compound computer vision workflow for efficient and automated immunohistochemical analysis of whole slide images.

Journal: Journal of clinical pathology
Published Date: Jul 1, 2023

Abstract

AIMS: Immunohistochemistry (IHC) assessment of tissue is a central component of the modern pathology workflow, but quantification is challenged by subjective estimates by pathologists or manual steps in semi-automated digital tools. This study integrates various computer vision tools to develop a fully automated workflow for quantifying Ki-67, a standard IHC test used to assess cell proliferation on digital whole slide images (WSIs).

Authors

  • Michael Kyung Ik Lee
    Laboratory Medicine & Pathobiology, University of Toronto Temerty Faculty of Medicine, Toronto, Ontario, Canada.
  • Madhumitha Rabindranath
    Transplant AI Initiative, Ajmera Transplant Program, University Health Network, Toronto, ON, Canada.
  • Kevin Faust
    Department of Computer Science, University of Toronto, 40 St. George Street, Toronto, ON, M5S 2E4, Canada.
  • Jennie Yao
    Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario, Canada.
  • Ariel Gershon
    Pathology, University Health Network, Toronto, Ontario, Canada.
  • Noor Alsafwani
    Pathology, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia.
  • Phedias Diamandis
    Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, M5S 1A8, Canada. p.diamandis@mail.utoronto.ca.

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