title: Detection and measurement of fetal abdominal contour in ultrasound images via local phase information and iterative randomized Hough transform.
abstract: Due to the characteristic artifacts of ultrasound images, e.g., speckle noise, shadows and intensity inhomogeneity, traditional intensity-based methods usually have limited success on the segmentation of fetal abdominal contour. This paper presents a novel approach to detect and measure the abdominal contour from fetal ultrasound images in two steps. First, a local phase-based measure called multiscale feature asymmetry (MSFA) is de ned from the monogenic signal to detect the boundaries of fetal abdomen. The MSFA measure is intensity invariant and provides an absolute measurement for the signi cance of features in the image. Second, in order to detect the ellipse that ts to the abdominal contour, the iterative randomized Hough transform is employed to exclude the interferences of the inner boundaries, after which the detected ellipse gradually converges to the outer boundaries of the abdomen. Experimental results in clinical ultrasound images demonstrate the high agreement between our approach and manual approach on the measurement of abdominal circumference (mean sign difference is 0.42% and correlation coef cient is 0.9973), which indicates that the proposed approach can be used as a reliable and accurate tool for obstetrical care and diagnosis.
authors.affiliation: Department of Computer Science and Engineering, The Chinese University of Hong Kong. E-mail: {wangwm, lzhu, ypchui, pheng}@cse.cuhk.edu.hk.
authors.forename: Weiming
authors.initials: W
authors.lastname: Wang
authors.forename: Jing
authors.initials: J
authors.lastname: Qin
authors.forename: Lei
authors.initials: L
authors.lastname: Zhu
authors.forename: Dong
authors.initials: D
authors.lastname: Ni
authors.forename: Yim-Pan
authors.initials: YP
authors.lastname: Chui
authors.forename: Pheng-Ann
authors.initials: PA
authors.lastname: Heng
mesh_terms: D000005:Abdomen / Q000196:embryology* / Q000473:pathology; D000465:Algorithms; D001185:Artificial Intelligence; D005260:Female; D006257:Head / Q000196:embryology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D010363:Pattern Recognition, Automated; D011247:Pregnancy; D015203:Reproducibility of Results; D012984:Software; D016216:Ultrasonography, Prenatal
keywords: Ultrasound images; fetal abdominal contour; iterative randomized Hough transform; multiscale feature asymmetry