The Canadian government, through its Strategic Innovation Fund, will invest up to $49 million to support the initiative, which, in addition to Kimia Lab and Huron Digital Pathology, consists of more than 70 partners from industry, academia, government organizations and not-for-profits. The consortium’s mandate is to accelerate the application of artificial intelligence and machine learning technologies to deliver better health outcomes, faster diagnoses and safer treatments.
Waterloo, Canada, June 03, 2019 --(PR.com)-- University of Waterloo's Kimia Lab announced today that it will participate in the $126 million Industry Consortium for Image Guided Therapy (ICIGT) led by the Sunnybrook Research Institute, with investment partnership from the Canadian government.
The Canadian government, through its Strategic Innovation Fund, will invest up to $49 million to support the ICIGT initiative, which, in addition to Kimia Lab and Huron Digital Pathology, consists of more than 70 partners from industry, academia, government organizations and not-for-profits. The consortium’s mandate is to accelerate the application of artificial intelligence and machine learning technologies to deliver better health outcomes, faster diagnoses and safer treatments that minimize side effects and the length of hospital stays.
Kimia and Huron’s project within ICIGT aims to develop intelligent algorithms for consensus building and auto-reporting in digital pathology to improve the speed, cost and accuracy of diagnosis. Huron, in technical partnership with the Kimia Lab, recently introduced the world’s first image search engine that connects pathologists to the vast knowledge contained in the world’s pathology reports.
“This is a historic opportunity to initiate a major change in diagnostic pathology,” says professor Hamid Tizhoosh, Director of Kimia Lab at University of Waterloo. “The AI-driven auto-reporting will be the main output of the project enabling diagnostic consensus by accessing large archives of histopathology images and learning from evidently diagnosed cases of the past.”
“With this project we will develop and bring to market novel technology that addresses a severe shortage of pathologists in Canada and around the world,” adds Patrick Myles, CEO of Huron Digital Pathology. “Together with our fellow ICIGT members, and with support from the Canadian government, we are further positioning Canada as a world leader in leading-edge medical technologies.”
About Kimia Lab
The Laboratory for Knowledge Inference in Medical Image Analysis (short Kimia Lab) is a research group hosted at the Faculty of Engineering, University of Waterloo, On, Canada. Kimia Lab, established in 2013, is a member of Waterloo Artificial Intelligence Institute and conducts research at the forefront of mass image data in medical archives using machine learning schemes with ultimate goal of extracting information that cannot only support a more speedy and accurate diagnosis and treatment of many diseases but also establish new quality assurance based on mining of existing evidence. The lab trains graduate and undergraduate students and annually hosts international visiting scholars. Professor Hamid Tizhoosh, Kimia Lab's director, is an expert in medical image analysis who has been working on different aspects of artificial intelligence since 1993. He is a faculty affiliate to the Vector Institute.
About Huron Digital Pathology
Based in St. Jacobs, ON, we are on a mission to transform glass slides into shareable knowledge. Our Scan, Index, and Search solution for pathology combines award-winning whole slide imaging hardware with powerful image search technology to connect pathologists, researchers and educators with the expertise of their colleagues to help speed up diagnosis and accelerate disease research. www.hurondigitalpathology.com
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