A research program focused on early detection and epidemiological research on skin cancer. We have been developing artificial intelligence and traditional machine learning methods for detecting skin cancer from photographs taken by digital cameras and smartphones. In order to complement the above technique, a melanoma probe based on polarization speckle was developed. The research team also investigates the prognosis and risk factors of melanoma.
Dr. Sunil Kalia, MD, MHSc, FAAD, FRCPC
Polarization speckles are the interference patterns created when a skin lesion is illuminated by laser light. The pattern encodes the surface and internal optical properties of the skin lesion.
In this project, we develop a handheld and easy-to-operate optical probe for detecting melanoma. Delivery of the technology is aimed at non-dermatologist healthcare providers, improving their diagnostic accuracy and reducing the number of referrals to the specialists.
Computer-aided systems for melanoma - The objectives of this project are to develop automated computer systems to help interpret the complex dermoscopic images with the ultimate aim of dissimilating the technique to non-dermatologist healthcare providers and, maybe, even patients.
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