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In this work, a deep learning approach for automated localization of carotid arteries in black blood contrast MR data is proposed. This is the first step in automated analysis of vessel wall imaging data. Carotid arteries supply oxygenated blood to the brain and are susceptible to atherosclerosis, so their vessel wall imaging is of significant importance in clinical evaluations. However, currently only qualitative assessment of VW imaging data relying on visual inspection is implemented in clinics that are not scaleable. Therefore, developing automated image processing tools to quantitatively analyze vessel wall imaging data can have a major clinical impact.
HashemizadehKolowri et al. (Wed,) studied this question.
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