Principal Investigator: Dr Owen Falzon, Centre for Biomedical Cybernetics
Co-Investigator: Mr Jean Gauci Centre for Biomedical Cybernetics
Co-Investigator: Prof. Kenneth Camilleri, Centre for Biomedical Cybernetics
Externally funded: RIDT Cancer Research Grant (2018) EUR 60,000
Early detection of skin cancer is crucial for increasing the effectiveness of treatment. Current methods for the differentiation between benign and malignant tumours are invasive. In this work we propose a computer aided diagnosis method that combines dynamic thermography with visual dermoscopic data for the detection of skin cancer and the non-invasive differentiation of benign and malignant tumors. We are going to study thermal and visual characteristics of the human skin to automatically distinguish between healthy and pathological skin regions. For this purpose, we are going to be looking at the application of advanced image processing, machine learning and data analysis techniques such as deep learning algorithms, which have already shown promise in improving detection rates when applied on dermoscopic images.
