Accurate Machine-Learning-Based classification of Leukemia from Blood Smear Images.

Journal: Clinical lymphoma, myeloma & leukemia
Published Date: Nov 1, 2021

Abstract

BACKGROUND: Conventional identification of blood disorders based on visual inspection of blood smears through microscope is time consuming, error-prone and is limited by hematologist's physical acuity. Therefore, an automated optical image processing system is required to support the clinical decision-making.

Authors

  • Kokeb Dese
    School of Biomedical Engineering, Jimma Institute of Technology, Jimma University, Jimma, Ethiopia-378.
  • Hakkins Raj
    School of Biomedical Engineering, Jimma Institute of Technology, Jimma University, Jimma, Ethiopia-378.
  • Gelan Ayana
    Department of Medical IT Convergence Engineering, Kumoh Institute of Technology, Gumi, Republic of Korea.
  • Tilahun Yemane
    Hematology and immunohematology course team, School of Medical Laboratory Sciences, Jimma University, Jimma, Ethiopia.
  • Wondimagegn Adissu
    Hematology and immunohematology course team, School of Medical Laboratory Sciences, Jimma University, Jimma, Ethiopia.
  • Janarthanan Krishnamoorthy
    School of Biomedical Engineering, Jimma Institute of Technology, Jimma University, Jimma, Ethiopia-378. Electronic address: jana.jk2006@gmail.com.
  • Timothy Kwa
    School of Biomedical Engineering, Jimma Institute of Technology, Jimma University, Jimma, Ethiopia-378. Electronic address: tkwa@ucdavis.edu.

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