Wiro Niessen
Title– Biomedical Imaging and Genetic Data Analysis With AI: Towards Precision Medicine
Abstract– The combination of big data and artificial intelligence are dramatically increasing the possibilities for prevention, cure, and care, and are changing the landscape of the healthcare system. Among the AI techniques, machine learning, and especially deep learning is a disruptive technology, impacting medical image acquisition, reconstruction, analysis, and image-based diagnosis and prognosis.
In this presentation, I will show the opportunities and challenges of big data analytics with AI techniques in medical imaging, also in combination with genetic and clinical data. Both conventional machine learning techniques, such as radiomics for tumor characterization, and deep learning techniques for studying brain aging and prognosis in dementia, will be addressed. Also the concept of deep imaging, a full integration of medical imaging and machine learning, will be discussed. Finally, I will address the challenges of how to successfully integrate these technologies in daily clinical workflow.
Bio– WiroNiessenis a professor in Biomedical Image Analysis and Machine Learning at Erasmus MC and Delft University of Technology. His interest is in the development, and validation of quantitative biomedical image analysis methods, and linking imaging and genetic data for improved disease diagnosis and prognosis. He supervised 52 PhD students in these fields. He is fellow and was president of the MICCAI Society, and CTO of Health-RI, which aims to develop a national health data infrastructure for research and innovation. In 2015 he received the Simon Stevin award, the largest prize in the Netherlands in Applied Sciences. In 2017 he was elected to the Royal Netherlands Academy of Arts and Sciences. In 2012 he founded Quantib, an AI company in medical imaging, where he is now the scientific lead.