medical image analysis, medical imaging, machine learning, healthcare
Hrvoje Bogunović obtained his BSc and MSc in Computer Science from the University of Zagreb, Croatia. He obtained his PhD in 2012 from the Universitat Pompeu Fabra (UPF), Barcelona, Spain. For his thesis he worked on medical image segmentation and shape analysis applied to blood vessels in the brain. After graduation he did a postdoc at the Iowa Institute for Biomedical Imaging (IIBI), University of Iowa, US, specializing in computational ophthalmic image analysis. He moved to Medical University of Vienna, Austria in 2015 to work on deep learning for retinal imaging. As of 2018 he is a Faculty there and as of 2021 a Director of Christian Doppler Lab for Artificial Intelligence in Retina.
His general research interests are in medical image computing and machine learning for healthcare. He is particularly interested in predicting disease progression and in knowledge discovery from large clinical longitudinal imaging datasets.
Ophthalmology is at the forefront of deep learning applications in medicine due to the ability to image the retina quickly and non-invasively. Deep learning recently enabled a first of its kind FDA approved fully autonomous diagnostic system and the field is attracting deep learning giants like Google, DeepMind and Baidu. I will show how deep learning is used for quantification of imaging biomarkers, automated diagnosis and progression prediction of prominent retinal diseases, the leading causes of blindness today.
Keywords: machine learning, medical image analysis, retina, optical coherence tomography