Automated cancer stem cell recognition in H&E stained tissue using convolutional neural networks and color deconvolution

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Aichinger W., Krappe S., ÇETİN A. E., Cetin-Atalay R., ÜNER A., Benz M., ...More

5th Digital Pathology Conference, Florida, United States Of America, 12 - 13 February 2017, vol.10140, (Full Text) identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume: 10140
  • Doi Number: 10.1117/12.2254036
  • City: Florida
  • Country: United States Of America
  • Hacettepe University Affiliated: Yes

Abstract

The analysis and interpretation of histopathological samples and images is an important discipline in the diagnosis of various diseases, especially cancer. An important factor in prognosis and treatment with the aim of a precision medicine is the determination of so-called cancer stem cells (CSC) which are known for their resistance to chemotherapeutic treatment and involvement in tumor recurrence. Using immunohistochemistry with CSC markers like CD13, CD133 and others is one way to identify CSC. In our work we aim at identifying CSC presence on ubiquitous Hematoxilyn & Eosin (H&E) staining as an inexpensive tool for routine histopathology based on their distinct morphological features.