title: Fully-automated identification and segmentation of aortic lumen from fetal ultrasound images.
abstract: Intrauterine growth restriction (IUGR) is a fetal condition that has been linked to an increase in cardiovascular mortality in the adult life. IUGR induces cardiovascular remodeling, including a decrease in aortic intima-media thickness (aIMT) which can be evaluated using fetal ultrasound imaging, potentially improving IUGR assessment and cardiovascular risk management. A necessary step for aIMT quantification is the identification of a region-of-interest (ROI) containing the lumen. This step is usually performed manually, even within the few semi-automated approaches to aIMT estimation. The aims of this study were to develop and test a fully-automated technique for lumen identification and segmentation from ultrasound images as a basis for aIMT quantification. The technique relies on convolution with a set of discriminative kernels learned from a training dataset using an AdaBoost classifier followed by segmentation based on anisotropic filtering and level-set methods. This approach was tested on 50 images acquired from 5 subjects: automatically extracted mean lumen width values were compared to reference ones manually obtained by an experienced interpreter. Results (R = 0.97) show that the proposed technique is accurate, suggesting that it could serve as a basis for fully-automated approaches to aIMT quantification.
authors.forename: Giacomo
authors.initials: G
authors.lastname: Tarroni
authors.forename: Silvia
authors.initials: S
authors.lastname: Visentin
authors.forename: Erich
authors.initials: E
authors.lastname: Cosmi
authors.forename: Enrico
authors.initials: E
authors.lastname: Grisan
mesh_terms: D001012:Aorta, Abdominal / Q000000981:diagnostic imaging*; D059168:Carotid Intima-Media Thickness; D005260:Female; D005317:Fetal Growth Retardation / Q000000981:diagnostic imaging; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D011247:Pregnancy; D011263:Pregnancy Trimester, Third; D016216:Ultrasonography, Prenatal / Q000379:methods*