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Coded Hemodynamic Imaging
My primary research contribution, coded hemodynamic imaging (CHI), is a highly novel and portable cardiovascular imaging system that is able to detect blood flow across large areas using specially "coded" light, enabling new ways for both preventive and acute physiological monitoring. This research brings together concepts from biophysical tissue optics, biomedical optics, embedded systems design and image and signal processing to enable first-of-its-kind monitoring. This research has attracted international media attention.
Nominated for Millenium Technology Prize, Technology Academy Finland |
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Automatic Melanoma Detection
Melanoma is the most lethal skin cancer, causing 75% of all skin-cancer related deaths, and yet clinical detection is still a very subjective process. In collaboration with our industry and clinical partners Agfa Healthcare and Toronto General Hospital, we developed novel biomedical image processing and machine learning algorithms for skin image correction, feature extraction and classification to create a computer aided diagnostic system.
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Metabolic Oxygen Uptake Prediction
The metabolic rate of oxygen uptake during activity can provide valuable insight into aerobic system function and early pre-clinical indications of degenerative diseases. However, traditional measuring techniques are invasive and prohibit daily monitoring. In collaboration with the Vascular Aging and Brain Health Lab, we developed a physiological regression model to estimate metabolic oxygen uptake using wearable sensor inputs.
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