A deep learning approach for automatic recognition of abnormalities in the cytoplasm of neutrophils.

Journal: Computers in biology and medicine
PMID: 38905894

Abstract

BACKGROUND AND OBJECTIVES: This study aims to develop and evaluate NeuNN, a system based on convolutional neural networks (CNN) and generative adversarial networks (GAN) for the automatic identification of normal neutrophils and those containing several types of inclusions or showing hypogranulation.

Authors

  • Kevin Barrera
    Technical University of Catalonia, Barcelona East Engineering School, Department of Mathematics, Barcelona, Spain. Electronic address: kevin.barrera@upc.edu.
  • José Rodellar
    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.

Keywords

External Resources

Popular Topics
Recent Journals