Automatic recognition of different types of acute leukaemia in peripheral blood by image analysis.

Journal: Journal of clinical pathology
PMID: 31256009

Abstract

AIMS: Morphological differentiation among different blast cell lineages is a difficult task and there is a lack of automated analysers able to recognise these abnormal cells. This study aims to develop a machine learning approach to predict the diagnosis of acute leukaemia using peripheral blood (PB) 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.
  • Santiago Alférez
    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.
  • Andrea Acevedo
    Mathematics, EEBE, Technical University of Catalonia, Barcelona, Catalonia, Spain.
  • José Rodellar
    Mathematics, EEBE, Technical University of Catalonia, Barcelona, Catalonia, Spain.

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