Recognition of peripheral blood cell images using convolutional neural networks.

Journal: Computer methods and programs in biomedicine
Published Date:

Abstract

BACKGROUND AND OBJECTIVES: Morphological analysis is the starting point for the diagnostic approach of more than 80% of hematological diseases. However, the morphological differentiation among different types of normal and abnormal peripheral blood cells is a difficult task that requires experience and skills. Therefore, the paper proposes a system for the automatic classification of eight groups of peripheral blood cells with high accuracy by means of a transfer learning approach using convolutional neural networks. With this new approach, it is not necessary to implement image segmentation, the feature extraction becomes automatic and existing models can be fine-tuned to obtain specific classifiers.

Authors

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