title: Segmentation of abdominal ultrasound images of the prostate using a priori information and an adapted noise filter.
abstract: This article discusses a method for the automatic segmentation of trans-abdominal ultrasound images of the prostate. Segmentation begins with the application of a filter to enhance the contours without modifying the image information. It combines adaptive morphological filtering and median filtering to detect the noise-containing regions and smooth them. A heuristic optimization algorithm searches for the contour initialized from a prostate model. The performance of the algorithm was tested by comparing the resulting contours with those obtained by manual segmentation. The average distance between the contours was 2.5 mm and the average coverage index was 93%.
authors.affiliation: Laboratoire de Biophysique, Centre Hospitalier Universitaire de Lille, Institut de Technologie Médicale, UPRES EA 1049, Pavillon Vancostenobel, CHRU 59037 Lille, France.
authors.forename: Nacim
authors.initials: N
authors.lastname: Betrouni
authors.forename: Maximilien
authors.initials: M
authors.lastname: Vermandel
authors.forename: David
authors.initials: D
authors.lastname: Pasquier
authors.forename: Salah
authors.initials: S
authors.lastname: Maouche
authors.forename: Jean
authors.initials: J
authors.lastname: Rousseau
mesh_terms: D000005:Abdomen / Q000000981:diagnostic imaging*; D000465:Algorithms; D005602:France; D006801:Humans; D008297:Male; D008953:Models, Anatomic; D011467:Prostate / Q000000981:diagnostic imaging*; D014463:Ultrasonography / Q000379:methods