A deep learning model (ALNet) for the diagnosis of acute leukaemia lineage using peripheral blood cell images.

Journal: Computer methods and programs in biomedicine
Published Date: Feb 12, 2021

Abstract

BACKGROUND AND OBJECTIVES: Morphological differentiation among blasts circulating in blood in acute leukaemia is challenging. Artificial intelligence decision support systems hold substantial promise as part of clinical practise in detecting haematological malignancy. This study aims to develop a deep learning-based system to predict the diagnosis of acute leukaemia using blood cell images.

Authors

  • Laura Boldú
    Biochemistry and Molecular Genetics, Biomedical Diagnostic Center, Hospital Clinic of Barcelona, Barcelona, Catalonia, Spain.
  • Anna Merino
    Biochemistry and Molecular Genetics, Biomedical Diagnostic Center, Hospital Clinic of Barcelona, Barcelona, Catalonia, Spain amerino@clinic.cat.
  • Andrea Acevedo
    Mathematics, EEBE, Technical University of Catalonia, Barcelona, Catalonia, Spain.
  • Angel Molina
    Biochemistry and Molecular Genetics, Biomedical Diagnostic Center, Hospital Clinic of Barcelona, Barcelona, Catalonia, Spain.
  • José Rodellar
    Mathematics, EEBE, Technical University of Catalonia, Barcelona, Catalonia, Spain.

Keywords

External Resources

Popular Topics
Recent Journals