title: Difference of Gaussians revolved along elliptical paths for ultrasound fetal head segmentation.
abstract: We present a fully automatic method to segment the skull from 2-D ultrasound images of the fetal head and to compute the standard biometric measurements derived from the segmented images. The method is based on the minimization of a novel cost function. The cost function is formulated assuming that the fetal skull has an approximately elliptical shape in the image and that pixel values within the skull are on average higher than in surrounding tissues. The main idea is to construct a template image of the fetal skull parametrized by the ellipse parameters and the calvarial thickness. The cost function evaluates the match between the template image and the observed ultrasound image. The optimum solution that minimizes the cost is found by using a global multiscale, multistart Nelder-Mead algorithm. The method was qualitatively and quantitatively evaluated using 90 ultrasound images from a recent segmentation grand challenge. These images have been manually analyzed by three independent experts. The segmentation accuracy of the automatic method was similar to the inter-expert segmentation variability. The automatically derived biometric measurements were as accurate as the manual measurements. Moreover, the segmentation accuracy of the presented method was superior to the accuracy of the other automatic methods that have previously been evaluated using the same data.
authors.affiliation: Department of Signal Processing, Tampere University of Technology, P.O. Box 553, Tampere FIN-33101, Finland.
authors.forename: Alessandro
authors.initials: A
authors.lastname: Foi
authors.affiliation: Department of Signal Processing, Tampere University of Technology, P.O. Box 553, Tampere FIN-33101, Finland.
authors.forename: Matteo
authors.initials: M
authors.lastname: Maggioni
authors.affiliation: Department of Signal Processing, Tampere University of Technology, P.O. Box 553, Tampere FIN-33101, Finland.
authors.forename: Antonietta
authors.initials: A
authors.lastname: Pepe
authors.affiliation: Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.
authors.forename: Sylvia
authors.initials: S
authors.lastname: Rueda
authors.affiliation: Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.
authors.forename: J Alison
authors.initials: JA
authors.lastname: Noble
authors.affiliation: Nuffield Department of Obstetrics and Gynaecology and Oxford Maternal and Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK.
authors.forename: Aris T
authors.initials: AT
authors.lastname: Papageorghiou
authors.affiliation: Department of Signal Processing, Tampere University of Technology, P.O. Box 553, Tampere FIN-33101, Finland. Electronic address: jussi.tohka@tut.fi.
authors.forename: Jussi
authors.initials: J
authors.lastname: Tohka
mesh_terms: D001699:Biometry / Q000379:methods*; D003627:Data Interpretation, Statistical; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016011:Normal Distribution; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012886:Skull / Q000000981:diagnostic imaging* / Q000196:embryology*; D016216:Ultrasonography, Prenatal / Q000379:methods*
keywords: Biparietal diameter; Energy minimization; Fetal biometry; Global optimization; Head circumference; Image analysis