An Automatic System for Computing Malaria Parasite Density in Thin Blood Films

  • Allisson Dantas Oliveira
  • Bruno M. Carvalho
  • Clara Prats
  • Mateu Espasa
  • Jordi Gomez i Prat
  • Daniel Lopez Codina
  • Jones Albuquerque
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10657)


Malaria is a major worldwide health problem, specially in countries with tropical climates and remote areas. In this paper, we present an automatic system for estimating malaria parasite density in thin blood smears. The proposed approach is based on simple image processing methods that can be implemented efficiently even on low budget devices. The method has been tested on images acquired under different illumination and acquisition setups and has produced encouraging results, achieving a sensitivity of 89.3%.


Malaria Parasite density Medical image processing 



This work was supported by the Graduate Program in Systems and Computer Science (PPgSC/UFRN) and funded by CAPES-Brazil.


  1. 1.
    CDC: Diagnostic procedures (2016). Accessed 06 Sept 2017
  2. 2.
    Chakrabortya, K., Chattopadhyayb, A., Chakrabarti, A., Acharyad, T., Dasguptae, A.: A combined algorithm for malaria detection from thick smear blood slides. Health Med. Inform. 6(1), 179 (2015)Google Scholar
  3. 3.
    Gonzalez, R., Woods, R.: Digital Image Processing. Pearson/Prentice Hall, Upper Saddle River (2008)Google Scholar
  4. 4.
    Kaewkamnerd, S., Uthaipibull, C., Intarapanich, A., Pannarut, M., Chaotheing, S., Tongsima, S.: An automatic device for detection and classification of malaria parasite species in thick blood film. BMC Bioinform. 13(Suppl 17), S18 (2012)CrossRefGoogle Scholar
  5. 5.
    Leal Neto, O.B., Cesar, A., Jones, A., Constanca, B.: The schisto track: a system for gathering and monitoring epidemiological surveys by connecting geographical information systems in real time. JMIR mHealth and uHealth 2, e10 (2014)CrossRefGoogle Scholar
  6. 6.
    Linder, N., Turkki, R., Walliander, M., Mårtensson, A., Diwan, V., Rahtu, E., Pietikainen, M., Lundin, M., Lundin, J.: A malaria diagnostic tool based on computer vision screening and visualization of Plasmodium falciparum candidate areas in digitized blood smears. PLoS ONE 9(8), e104855 (2014)CrossRefGoogle Scholar
  7. 7.
    Moody, A.: Rapid diagnostic tests for malaria parasites. Clin. Microbiol. Rev. 15(1), 66–78 (2002)CrossRefGoogle Scholar
  8. 8.
    Oliveira, D.A., Prats, C., Espasa, M., Zarzuela Serrat, F., Montañola Sales, C., Silgado, A., Codina, L.D., Arruda, E.M., Gomez i Prat, J., Albuquerque, J.: The malaria system microapp: a new, mobile device-based tool for malaria diagnosis. JMIR Res. Protoc. 6(4), e70 (2017)CrossRefGoogle Scholar
  9. 9.
    World Health Organization: World malaria report 2014. Technical report, World Health Organization (2014)Google Scholar
  10. 10.
    Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9(1), 62–66 (1979)MathSciNetCrossRefGoogle Scholar
  11. 11.
    Pirnstill, C.W., Cote, G.L.: Malaria diagnosis using a mobile phone polarized microscope. Sci. Rep. 5, 13368 (2015)CrossRefGoogle Scholar
  12. 12.
    WHO Press: Basic malaria microscopy. World Health Organization, Geneva, Switzerland (1991)Google Scholar
  13. 13.
    Ross, N., Pritchard, C., Rubin, D., Dusao, A.: Automated image processing method for the diagnosis and classification of malaria on thin blood smears. Med. Biol. Eng. Comput. 44(5), 427–436 (2006)CrossRefGoogle Scholar
  14. 14.
    Szeliski, R.: Computer Vision: Algorithms and Applications. Texts in Computer Science. Springer, London (2010). MATHGoogle Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Informatics and Applied MathematicsUFRNNatalBrazil
  2. 2.BarcelonaTechUniversitat Politècnica de CatalunyaBarcelonaSpain
  3. 3.Microbiology DepartmentVall dHebron University HospitalBarcelonaSpain
  4. 4.Department of Statistics and InformaticsUFRPERecifeBrazil

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