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

Generation of realistic simulated B-mode image texture with a GAN.

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)
DOI
The intima-media complex of the common carotid artery is considered the sentinel of a silent killer disease called atherosclerosis. Morphological biomarkers such as the intima-media thickness are already exploitable, but dynamic biomarkers, which reflect tissue deformation over the cardiac cycle, remain to be validated. Recent motion estimation methods seek to quantify compression, shear, and elongation coefficients, but their clinical applicability has not yet been well defined, and their actual accuracy is difficult to assess due to the absence of ground truth. This lack of reference also is the main limitation to explore fully supervised deep learning methods that have shown great potential in other applications. With this in mind, we propose a simulation pipeline to produce realistic in silico sequences, by combining a physics-based simulator with a post-processing based on a generative adversarial network.
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Publikationstyp Artikel: Konferenzbeitrag
Schlagwörter Carotid Artery ; Deep Learning ; Domain Adaptation ; Generative Adversarial Network ; Ultrasound Simulation
Sprache englisch
Veröffentlichungsjahr 2022
HGF-Berichtsjahr 2022
ISSN (print) / ISBN 1948-5719
e-ISSN 1948-5727
Konferenztitel 2022 IEEE International Ultrasonics Symposium (IUS)
Konferzenzdatum 10-13 October 2022
Konferenzort Venice, Italy
Quellenangaben Band: , Heft: , Seiten: 4 Artikelnummer: , Supplement: ,
Verlag Ieee
Verlagsort 345 E 47th St, New York, Ny 10017 Usa
Institut(e) Institute of Biological and Medical Imaging (IBMI)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-505500-001
Förderungen LABEX PRIMES of Universite de Lyon, within the program "Investissements d'Avenir"
NL's doctoral grant
DOI 10.1109/IUS54386.2022.9958665
WOS ID 000896080400478
Scopus ID 85143832445
Erfassungsdatum 2022-12-21
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