Detection of Plasmodium Parasites from Images of Thin Blood Smears using Artificial Neural Networks

Authors

  • Dalia Mahmoud Adam Department of Electronic Engineering, Faculty of Engineering, Khartoum, Sudan.
  • Abdalla Eltoum Ali Department of Clinical Chemistry. Faculty of Medical Laboratory Sciences. Alzaiem Alazhari University. Khartoum, Sudan

Keywords:

Malaria Parasite, ElmanNetworks, Graphical User Interface (GUI), Computer Aided Diagnosis (CAD).

Abstract

Despite all the efforts of all associations and health organizations around the world, the infections and deaths from the malaria disease are remain high, especially in the developing countries. Accurate and correct diagnosis of malaria helps in getting the appropriate treatment. This paper contains a design for automatic diagnostic system for malaria using Artificial Neural Networks (ANNs). Different image samples negative and positive were collected, and then ANN was designed and trained on it. The ANN type was Elman network and it achieved excellent performance in the test.

References

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Published

2016-03-01

How to Cite

Adam, D. M., & Ali, A. E. (2016). Detection of Plasmodium Parasites from Images of Thin Blood Smears using Artificial Neural Networks. American Scientific Research Journal for Engineering, Technology, and Sciences, 17(1), 144–149. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/1418

Issue

Vol. 17 No. 1 (2016)

Section

Articles

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