Automated Histology Analysis: Opportunities for signal processing

Michael T. McCann, John A. Ozolek, Carlos A. Castro, Bahram Parvin, Jelena Kovacevic

Research output: Contribution to journalReview article

Abstract

Histology is the microscopic inspection of plant or animal tissue. It is a critical component in diagnostic medicine and a tool for studying the pathogenesis and biology of processes such as cancer and embryogenesis. Tissue processing for histology has become increasingly automated, drastically increasing the speed at which histology labs can produce tissue slides for viewing. Another trend is the digitization of these slides, allowing them to be viewed on a computer rather than through a microscope. Despite these changes, much of the routine analysis of tissue sections remains a painstaking, manual task that can only be completed by highly trained pathologists at a high cost per hour. There is, therefore, a niche for image analysis methods that can automate some aspects of this analysis. These methods could also automate tasks that are prohibitively time-consuming for humans, e.g., discovering new disease markers from hundreds of whole-slide images (WSIs) or precisely quantifying tissues within a tumor.

Original languageEnglish (US)
Article number6975290
Pages (from-to)78-87
Number of pages10
JournalIEEE Signal Processing Magazine
Volume32
Issue number1
DOIs
StatePublished - Jan 1 2015

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Keywords

  • Biological tissues
  • Biomedical imaging
  • Biomedical signal processing
  • Biopsy
  • Histology
  • Image analysis
  • Image color analysis
  • Microscopy
  • Signal processing
  • Visualization

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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