Computer-vision-based technology for fast, accurate and cost effective diagnosis of malaria
Related Experiment Video
Updated: Oct 23, 2026

In Vivo Tracking of Edema Development and Microvascular Pathology in a Model of Experimental Cerebral Malaria Using Magnetic Resonance Imaging
Published on: June 8, 2017
Bina Srivastava1, Anupkumar R Anvikar2, Susanta K Ghosh3
1National Institute of Malaria Research, Sector 8 Dwarka, New Delhi, 110 077, India. shbira@gmail.com.
Background:
Microscopy has long been considered to be the gold standard for diagnosis of malaria despite the introduction of newer assays. However, it has many challenges like requirement of trained microscopists and logistic issues. A vision based device that can diagnose malaria, provide speciation and estimate parasitaemia was evaluated.
Methods:
The device was evaluated using samples from 431 consented patients, 361 of which were initially screened by RDT and microscopy and later analysed by PCR. It was a prospective, non-randomized, blinded trial. Quantification of parasitaemia was performed by two experienced technicians. Samples were subjected to diagnosis by Sight Dx digital imaging scanning.
Results:
The sensitivity and specificity of the SightDx P1 device for analysed samples were found to be 97.05 and 96.33%, respectively, when compared to PCR. When compared to microscopy, sensitivity and specificity were found to be 94.4 and 95.6%, respectively. The device was able to speciate 73.3% of the PCR Plasmodium falciparum positive samples and 91.4% of PCR Plasmodium vivax positive samples.
Conclusion:
The ability of the device to detect parasitaemia as compared with microscopy, was within 50% in 71.3% of cases and demonstrated a correlation coefficient of 0.89.
More Related Videos
10:50Detection and Quantification of Plasmodium falciparum in Aqueous Red Blood Cells by Attenuated Total Reflection Infrared Spectroscopy and Multivariate Data Analysis
Published on: November 2, 2018
08:20Author Spotlight: AI-Driven Trypanosome Species Detection from Microscopic Images
Published on: October 27, 2023
Related Concept Videos
Rapid Identification of Pathogens
Automated Microbial Diagnostics