Cardiovascular MR image processing using deep learning

The project aims to use advanced magnetic resonance imaging and image processing methods to improve the understanding of atherosclerotic disease in the carotid arteries. Data is currently being acquired in several hundred patients with carotid atherosclerosis and age- and sex-matched controls. Deep learning is used to automatically segment the carotid arteries in MR images and subsequently use these segmentations to extract data on hemodynamics effects on the vessel wall as well as the composition of vessel wall.

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