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Deep Learning to Inform Medical Diagnoses
SFU researchers are working to create computer vision and data analysis tools that can help support medical professionals and support their decision-making regarding life-saving cancer diagnosis and treatments.
Computing Science professor, Ghassan Hamarneh leads the Medical Image Analysis Research Group, which focuses on developing artificial intelligence technologies for healthcare and biomedical applications, with a focus on computer vision and machine learning techniques for automatically interpreting biomedical images. His team is using machine learning and deep learning techniques to examine super-resolution microscopic images of cell structures and determine which features stand out.
Accurate interpretations of medical images can inform diagnosis, guide endoscopic surgery, evaluate blood flow, and perform a host of other functions.
Machine learning and imaging technologies can detect minimal changes in cancerous tumours with quantifiable, reproducible results. Such precision technologies can take some of the workload off medical professionals work as second opinions for medical professionals and point out anomalies that might have been missed.