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Laine, N.* ; Zahnd, G. ; Liebgott, H.* ; Orkisz, M.*

Segmenting the carotid-artery wall in ultrasound image sequences with a dual-resolution U-net.

In: (2022 IEEE International Ultrasonics Symposium (IUS), 10-13 October 2022, Venice, Italy). 345 E 47th St, New York, Ny 10017 Usa: Ieee, 2022.:4 (IEEE International Ultrasonics Symposium, IUS)

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Thickening of intima-media complex in the common carotid artery is a biomarker of atherosclerosis. To automatically measure this thickness, we propose a region-based segmentation method, involving a supervised deep-learning approach based on the dilated U-net architecture, named caroSegDeep. It was trained and evaluated using 5-fold cross-validation on two open-access databases containing a total of 2676 annotated images. Compared with the methods already evaluated on these databases, caroSegDeep established a new benchmark and achieved a mean absolute error twice smaller than the inter-observer variability.

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