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as soon as is submitted to ZB.
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)
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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Publication type
Article: Conference contribution
Keywords
Atherosclerosis ; Carotid Artery ; Deep Learning ; Segmentation ; Ultrasound; Intima-media Complex; Segmentation; Atherosclerosis
ISSN (print) / ISBN
1948-5719
e-ISSN
1948-5727
Conference Title
2022 IEEE International Ultrasonics Symposium (IUS)
Conference Date
10-13 October 2022
Conference Location
Venice, Italy
Quellenangaben
Article Number: 4
Publisher
Ieee
Publishing Place
345 E 47th St, New York, Ny 10017 Usa
Non-patent literature
Publications
Institute(s)
Institute of Biological and Medical Imaging (IBMI)
Grants
LABEX PRIMES of Universite de Lyon, within the program "Investissements d'Avenir"
via NL's doctoral grant
via NL's doctoral grant