ArticleMalaria journal2010
Automated estimation of parasitaemia of Plasmodium yoelii-infected mice by digital image analysis of Giemsa-stained thin blood smears.
Article in Malaria journal, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Semi-synthesis of the C-terminal region ofRSC chemical biology · 2026Article
- Application of Machine Learning in a Rodent Malaria Model for Rapid, Accurate, and Consistent Parasite Counts.The American journal of tropical medicine and hygiene · 2024Article
- The Multistage Antimalarial Compound Calxinin PerturbatesPharmaceutics · 2022Article
- Computational Methods for Automated Analysis of Malaria Parasite Using Blood Smear Images: Recent Advances.Computational intelligence and neuroscience · 2022Review
- Advances and challenges in automated malaria diagnosis using digital microscopy imaging with artificial intelligence tools: A review.Frontiers in microbiology · 2022Review
- Multistage antiplasmodial activity of hydroxyethylamine compounds,RSC advances · 2020Article
- Strain-transcending neutralization of malaria parasite by antibodies against Plasmodium falciparum enolase.Malaria journal · 2018Article
- Image analysis and machine learning for detecting malaria.Translational research : the journal of laboratory and clinical medicine · 2018Review
- Synergistic blending of high-valued heterocycles inhibits growth of Plasmodium falciparum in culture and P. berghei infection in mouse model.Scientific reports · 2017Article
- Stearylamine Liposomal Delivery of Monensin in Combination with Free Artemisinin Eliminates Blood Stages of Plasmodium falciparum in Culture and P. berghei Infection in Murine Malaria.Antimicrobial agents and chemotherapy · 2015Article
- Hemozoin-generated vapor nanobubbles for transdermal reagent- and needle-free detection of malaria.Proceedings of the National Academy of Sciences of the United States of America · 2014Article
- An image analysis algorithm for malaria parasite stage classification and viability quantification.PloS one · 2013Article
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4 authors.
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Abstract
backgroundParasitaemia, the percentage of infected erythrocytes, is used to measure progress of experimental Plasmodium infection in infected hosts. The most widely used technique for parasitaemia determination is manual microscopic enumeration of Giemsa-stained blood films. This process is onerous, time consuming and relies on the expertise of the experimenter giving rise to person-to-person variability. Here the development of image-analysis software, named Plasmodium AutoCount, which can automatically generate parasitaemia values from Plasmodium-infected blood smears, is reported.
methodsGiemsa-stained blood smear images were captured with a camera attached to a microscope and analysed using a programme written in the Python programming language. The programme design involved foreground detection, cell and infection detection, and spurious hit filtering. A number of parameters were adjusted by a calibration process using a set of representative images. Another programme, Counting Aid, written in Visual Basic, was developed to aid manual counting when the quality of blood smear preparation is too poor for use with the automated programme.
resultsThis programme has been validated for use in estimation of parasitemia in mouse infection by Plasmodium yoelii and used to monitor parasitaemia on a daily basis for an entire challenge infection. The parasitaemia values determined by Plasmodium AutoCount were shown to be highly correlated with the results obtained by manual counting, and the discrepancy between automated and manual counting results were comparable to those found among manual counts of different experimenters.
conclusionsPlasmodium AutoCount has proven to be a useful tool for rapid and accurate determination of parasitaemia from infected mouse blood. For greater accuracy when smear quality is poor, Plasmodium AutoCount, can be used in conjunction with Counting Aid.
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