Professor Clinton Fookes
harnesses his expertise in computer vision and artificial intelligence to improve diagnosis and treatment of disease through automated analysis of medical imaging. He develops intelligent systems that can interpret complex biosignals, such as electroencephalograms (EEGs) and electrocardiograms (ECGs), which are critical for diagnosing neurological and cardiovascular conditions. Professor Fookes has devised neural memory networks that outperform existing models in detecting challenging medical anomalies, such as classifying tumour types based on MRIs. He has created generative models that produce realistic biosignals, which can train models when real data is scarce due to issues such as privacy and cost. Other innovations include more-accurate techniques for identifying healthy tissue at risk of exposure during radiotherapy, which improves precision during treatment. Collectively, his work has the potential to transform how machines interpret medical imagery.
Find Prof Fookes QUT Academic Profile here.
Read and download the Precision Imaging Capability Statement
