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A review on automated diagnosis of malaria parasite in microscopic blood smears images

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Abstract

Malaria is a life-threatening disease caused by parasite of genus plasmodium, which is transmitted through the bite of infected Anopheles. A rapid and accurate diagnosis of malaria is demanded for proper treatment on time. Mostly, conventional microscopy is followed for diagnosis of malaria in developing countries, where pathologist visually inspects the stained slide under light microscope. However, conventional microscopy has occasionally proved inefficient since it is time consuming and results are difficult to reproduce. Alternate techniques for malaria diagnosis based on computer vision were proposed by several researchers. The aim of this paper is to review, analyze, categorize and address the recent developments in the area of computer aided diagnosis of malaria parasite. Research efforts in quantification of malaria infection include normalization of images, segmentation followed by features extraction and classification, which were reviewed in detail in this paper. At the end of review, the existent challenges as well as possible research perspectives were discussed.

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Acknowledgements

This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2016R1D1A1A09919551).

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Authors and Affiliations

  1. Digital Image Processing Laboratory, Department of Computer Science, Islamia College Peshawar, Peshawar, Pakistan

    Zahoor Jan, Arshad Khan, Muhammad Sajjad & Khan Muhammad

  2. Intelligent Media Laboratory, Digital Contents Research Institute, College of Electronics and Information Engineering, Sejong University, Seoul, Republic of Korea

    Khan Muhammad

  3. Department of Media Software, Sungkyul University, Anyang, Republic of Korea

    Seungmin Rho

  4. Department of Computer Science and Engineering, Sejong University, Seoul, Republic of Korea

    Irfan Mehmood

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  1. Zahoor Jan
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  2. Arshad Khan
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  3. Muhammad Sajjad
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  4. Khan Muhammad
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  5. Seungmin Rho
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  6. Irfan Mehmood
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Correspondence to Irfan Mehmood.

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Jan, Z., Khan, A., Sajjad, M. et al. A review on automated diagnosis of malaria parasite in microscopic blood smears images. Multimed Tools Appl 77, 9801–9826 (2018). https://doi.org/10.1007/s11042-017-4495-2

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