Evaluation of deep learning training strategies for the classification of bone marrow cell images.

Journal: Computer methods and programs in biomedicine
PMID: 37979517

Abstract

BACKGROUND AND OBJECTIVE: The classification of bone marrow (BM) cells by light microscopy is an important cornerstone of hematological diagnosis, performed thousands of times a day by highly trained specialists in laboratories worldwide. As the manual evaluation of blood or BM smears is very time-consuming and prone to inter-observer variation, new reliable automated systems are needed.

Authors

  • Stefan Glüge
    Institute of Computational Life Sciences, Zurich University of Applied Sciences, Schloss 1, 8820 Wädenswil, Switzerland. Electronic address: stefan.gluege@zhaw.ch.
  • Stefan Balabanov
    Department of Medical Oncology and Haematology, University Hospital Zurich and University of Zurich, Rämistrasse 100, 8091 Zurich, Switzerland.
  • Viktor Hendrik Koelzer
    Department of Pathology and Molecular Pathology, University Hospital Zurich and University of Zurich, Schmelzbergstrasse 12, 8091 Zurich, Switzerland.
  • Thomas Ott
    Institute of Computational Life Sciences, Zurich University of Applied Sciences, Schloss 1, 8820 Wädenswil, Switzerland.

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