Scientists, including one of Indian-origin, claim to have developed a new innovative system for accurately diagnosing malaria infection.
The method is based on computer vision algorithms similar to those used in facial recognition systems combined with visualisation of only the diagnostically most relevant areas.
A thin layer of blood smeared on a microscope slide is first digitised. The algorithm analyses more than 50,000 red blood cells per sample and ranks them according to the probability of infection.
Then the programme creates a panel containing images of more than a hundred most likely infected cells and presents that panel to the user. The final diagnosis is done by a health-care professional based on the visualised images.
By utilising a set of existing, already diagnosed samples, the researchers at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, and Karolinska institutet, Stockholm, were able to show that the accuracy of this method was comparable to the quality criteria defined by the World Health Organisation.
In the test setting, more than 90 per cent of the infected samples were accurately diagnosed based on the panel.
The few problematic samples were of low quality and in a true diagnostic setting would have led to further analyses.
“We are not suggesting that the whole malaria diagnostic process could or should be automated. Rather, our aim is to develop methods that are significantly less labour intensive than the traditional ones and have a potential to considerably increase the throughput in malaria diagnostics,” said Research Director Johan Lundin from FIMM.
“The equipment needed for digitisation of the samples is a challenge in developed countries. In the next phase of our project we will test the system in combination with inexpensive mobile microscopy devices that our group has also developed,” said the shared first author of the article Nina Linder from FIMM.
The developed support system can be applied in various other fields of medicine. In addition to other infectious diseases such as tuberculosis, the research group is planning to test the system for cancer diagnostics in tissue samples.
“The new method of imaging and analysis can revolutionise the point of care diagnostics of not only malaria but also several diseases where diagnosis depends on microscopy. The action may lead to ‘market rupture’ in the field of disease diagnostics,” said Professor Vinod Diwan from Karolinska.
The research was described in the journal PLOS One.
