Validation of Cartilage Segmentation Accuracy using Deep Learning

Osteoarthritis is a degenerative disease that affects the majority of seniors and costs the Canadian economy > $30 Billion/year. The hallmark of osteoarthritis is damaged cartilage. Our understanding of how and why cartilage degenerates is not well understood. In order to identify how to stop or prevent cartilage degeneration we must have accurate and reproducible ways to measure cartilage health. The industry partner NeuralSeg has developed an algorithm that utilizes a form of artificial intelligence to measure cartilage health. The proposed research project consists of two phases. Phase one identifies the accuracy of the analysis performed by the algorithm. Phase two identifies how reproducible the measures of cartilage health are. These benchmarks are a necessary step before this technology can be used for research and eventually be deployed to the clinic.

Intern: 
Anthony Gatti
Faculty Supervisor: 
Monica R. Maly
Province: 
Ontario
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