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Malaria Diagnostic Platform, Light Microscopy Enhancements/Digital Microscopy

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Encyclopedia of Malaria
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Synonyms

Microsocpy; Enhancements; Artificial intellegence; Automation; Machine-learning; Image recognition

Definition

Light microscopy has long been a mainstay of malaria diagnosis but has significant drawbacks that reduce its accuracy. Various modifications have been developed and are under development, to improve microscopy accuracy, including modifications to reagents and imaging systems, and automated image processing to reduce the human element contributing to poor performance.

Introduction

Examination of Giemsa-stained blood films has been a standard of malaria diagnosis for more than 100 years. When performed by well-trained technicians, the method has high accuracy for malaria diagnosis and gives a range of information including species and parasite count. In addition, Giemsa smear microscopy (GSM) and use of similar Romanowsky stains (RSM) uses only commonly available laboratory infrastructure, and can be done in batches with good throughput. These advantages have made GSM...

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References

  • Ashraf S, Kao A, Hugo C, et al. Developing standards for malaria microscopy: external competency assessment for malaria microscopists in the Asia-Pacific. Malar J. 2012;24:352.

    Article  Google Scholar 

  • Coleman RE, Maneechai N, Rachaphaew N, et al. Comparison of field and expert laboratory microscopy for active surveillance for asymptomatic Plasmodium falciparum and Plasmodium vivax in western Thailand. Am J Trop Med Hyg. 2002;67:141–4.

    Article  PubMed  Google Scholar 

  • Das DK, Mukherjee R, Chakraborty C. Computational microscopic imaging for malaria parasite detection: a systematic review. J Microsc. 2015;260:1–19.

    Article  CAS  PubMed  Google Scholar 

  • Delahunt C, Horning MP, Wilson BK, Proctor JL, Hegg MC. Limitations of haemozoin-based diagnosis of Plasmodium falciparum using dark-field microscopy. Malar J. 2014;13:147.

    Article  PubMed  PubMed Central  Google Scholar 

  • Eshel Y, Houri-Yafin A, Benkuzari H, et al. Evaluation of the parasight platform for malaria diagnosis. J Clin Microbiol. 2017;55:768–75.

    Article  PubMed  PubMed Central  Google Scholar 

  • Kahama-Maro J, D’Acremont V, Mtasiwa D, Genton B, Lengeler C. Low quality of routine microscopy for malaria at different levels of the health system in Dar es Salaam. Malar J. 2011;10:332.

    Article  PubMed  PubMed Central  Google Scholar 

  • Keiser J, Utzinger J, Premji Z, Yamagata Y, Singer BH. Acridine Orange for malaria diagnosis: its diagnostic performance, its promotion and implementation in Tanzania, and the implications for malaria control. Ann Trop Med Parasitol. 2002;96:643–54.

    Article  CAS  PubMed  Google Scholar 

  • Mehanian C, Jaiswal M, Delahunt C, et al. Computer-automated malaria diagnosis and quantitation using convolutional neural networks. In: 2017 IEEE international conference on computer vision workshop (ICCVW); 2017 Oct 22–29; Venice; 2017. pp. 116–25.

    Google Scholar 

  • Shah J, Mark O, Weltman H, et al. Fluorescence in situ hybridization (FISH) assays for diagnosing malaria in endemic areas. PLoS One. 2015;10(9):e0136726.

    Article  PubMed  PubMed Central  Google Scholar 

  • Tek FB, Dempster AG, Kale I. Computer vision for microscopy diagnosis of malaria. Malar J. 2009;8:153.

    Article  PubMed  PubMed Central  Google Scholar 

  • WHO. World malaria report 2014. Geneva: World Health Organization; 2014.

    Google Scholar 

  • WHO. Malaria microscopy quality assurance manual – version 2. Geneva: World Health Organization; 2016.

    Google Scholar 

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Correspondence to Ben Wilson .

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Wilson, B., Bell, D. (2018). Malaria Diagnostic Platform, Light Microscopy Enhancements/Digital Microscopy. In: Kremsner, P., Krishna, S. (eds) Encyclopedia of Malaria. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8757-9_106-1

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  • DOI: https://doi.org/10.1007/978-1-4614-8757-9_106-1

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  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-8757-9

  • Online ISBN: 978-1-4614-8757-9

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