title: A geometric snake model for segmentation of medical imagery.
abstract: In this note, we employ the new geometric active contour models formulated in [25] and [26] for edge detection and segmentation of magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound medical imagery. Our method is based on defining feature-based metrics on a given image which in turn leads to a novel snake paradigm in which the feature of interest may be considered to lie at the bottom of a potential well. Thus, the snake is attracted very quickly and efficiently to the desired feature.
authors.affiliation: Department of Electrical Engineering, University of Minnesota, Minneapolis 55455, USA.
authors.forename: A
authors.initials: A
authors.lastname: Yezzi
authors.forename: S
authors.initials: S
authors.lastname: Kichenassamy
authors.forename: A
authors.initials: A
authors.lastname: Kumar
authors.forename: P
authors.initials: P
authors.lastname: Olver
authors.forename: A
authors.initials: A
authors.lastname: Tannenbaum
mesh_terms: D000465:Algorithms; D003952:Diagnostic Imaging / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D015233:Models, Statistical; D008962:Models, Theoretical; D012815:Signal Processing, Computer-Assisted