Malaria Diagnostic Platform, Light Microscopy Enhancements/Digital Microscopy
- 90 Downloads
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.
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...
- 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
- 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