UQ, SNP speed up pathology workflows
The University of Queensland and Sullivan Nicolaides Pathology (SNP) have automated a microscope scanning and analysis system in Brisbane that has been tested, implemented and accredited ready for rollout around the world.
The result of a decade-long research project, the development will see patients receive faster and more accurate pathology results.
UQ Professor of AI Brian Lovell said, “This digital pathology technology processes thousands of tests a day and has been accredited by the National Association of Testing Authorities (NATA).
“At times the system can increase the productivity of pathologists and scientists by factors of 10 or more.
“The system also provides the ability to obtain second opinions via telepathology and dramatically improves record keeping and access of historical records, as the glass slides are no longer needed to be archived for years.”
SNP Chief Executive Officer Dr Michael Harrison said the technology is a game changer in many areas of health care.
“SNP laboratories in Brisbane are already using the system to improve the speed and accuracy of diagnoses,” Harrison said.
“Our scientists now use a digitised image often with associated AI instead of being tied to a microscope for many hours.
“This is the most significant change in the performance of morphological tests for decades.”
Lovell said there had previously been major problems with obtaining sharp, in-focus images with no human intervention.
“Digital pathology images are often thousands of times larger than typical digital photos,” he said.
“This had meant microscopy for diagnosing from tissue, blood and other specimen types was unable to be automated until now.
“Our active scanner knows what it is scanning and where it should scan, using image analysis and artificial intelligence.
“This greatly increases image quality and reduces file size.”
Dr Dean Moss, CEO of UQ commercialisation company UniQuest, said the technology demonstrated the benefits of industry collaboration with innovative researchers.
This research is supported by SNP, two Australian Research Council projects, and an Advance Queensland Fellowship from the Queensland Government.
The technology won the Business and Industry Solution category at the recent Queensland iAwards, progressing to the national finals later this year.
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