Deep Learning for Smartphone-Based Malaria Parasite Detection in Thick Blood Smears.

Journal: IEEE journal of biomedical and health informatics
PMID:

Abstract

OBJECTIVE: This work investigates the possibility of automated malaria parasite detection in thick blood smears with smartphones.

Authors

  • Feng Yang
  • Mahdieh Poostchi
    Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, Maryland, United States.
  • Hang Yu
  • Zhou Zhou
  • Kamolrat Silamut
    Mahidol-Oxford Tropical Medicine Research Unit, Mahidol University, Bangkok, Thailand.
  • Jian Yu
    Key laboratory of Transplantation, Chinese Academy of Medical Sciences, Tianjin, 300192, China; Tianjin Key Laboratory for Organ Transplantation, Tianjin First Center Hospital, Tianjin, 300192, China; Department of Liver Transplantation, Tianjin Medical University First Center Clinical College, Tianjin, 300192, China; Tianjin Key Laboratory of Molecular and Treatment of Liver Cancer, Tianjin First Center Hospital, Tianjin, 300192, China.
  • Richard J Maude
    University of Oxford, Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, Oxford, United Kingdom.
  • Stefan Jaeger
    Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, Maryland, United States.
  • Sameer Antani
    Computational Health Research Branch, National Library of Medicine, National Institutes of Health, Bethesda, MD, USA.