QUT has humanity's most significant parasitic disease in its robotic sights.
Roboticist Professor Jonathan Roberts, surgeon Professor Ross Crawford and biologist Dr Anjali Jaiprakash are together creating a low-cost medical device that uses machine learning and robotic vision to diagnose malaria far more quickly than current methods allow.
Spread through the bite of infected mosquitoes, World Health Organization figures show half the world's population - 3.4 billion - is at risk of contracting malaria, which kills one child in Africa every minute.
Dr Jaiprakash, from QUT's Science and Engineering Faculty, said malaria is curable provided the victim is diagnosed and treated promptly and correctly.
"Unfortunately, getting that early diagnosis is particularly difficult in developing nations," Dr Jaiprakash said.
"Currently, a patient's blood sample must be sent to a laboratory, where a highly skilled health professional analyses it using to find out the type and the volume of malaria parasites present.
"That takes time, especially when the victim is in a remote community.
"We've developing a low-cost diagnostic device that will tell health workers in the field immediately if the parasite is present in the blood, and at what density, so that treatment can begin immediately."
Dr Jaiprakash said the microscope system attaches to a smart phone and compares the stained blood sample to a comprehensive image database of infected blood samples.
The system uses computer vision to 'see' and compare the blood sample. It also learns from each sample it takes, adding that information to its ever-growing database of comparable images so that it can more quickly diagnose the next patient.
Best of all, the system doesn't require internet access, so it can be used effectively in the remotest of communities.
"This technology will be life-changing for literally half of humanity," Dr Jaiprakash said.
"The system requires minimal training - the kits can be shipped to regions suffering outbreaks quickly and cheaply, which will also help to minimise the outbreak.
"Not only will it allow fast treatment for those infected - the system will help reduce the emergence and spread of drug resistance by reserving antimalarial medication for those who actually have the disease."
The team hopes to have a working model of the malaria-detecting device by the end of this year.
The project is one of several underway as part of a new collaborative research focus for the Australian Centre for Robotic Vision and QUT's Medical Engineering Research Facility, Science and Engineering Faculty and Institute of Health and Biomedical Innovation.
Roboticist Professor Jonathan Roberts said the technologies being developed at QUT could be adapted for other diseases and procedures.
"We're researching a low-cost device to diagnose diabetic retinopathy, an arthroscopy robot and a 3-D scanning platform we believe will help surgeons and their pathology colleagues remove bone tumours more accurately," Professor Roberts said.
"The field of robotics is evolving rapidly and we are excited by the prospect of applying QUT's world-leading robotic vision research to solutions that will improve the lives of people across the world while reducing the cost of healthcare."
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