title: Airway segmentation and measurement in CT images.
abstract: In this paper we describe a methodology for constructing the airways from Cone Beam CT data and representing changes before and after a medical procedure. A seed region is automatically detected for the first CT slice using a heuristic algorithm incorporating morphological filtering. Our approach then extracts relevant contours on 3D slices by using gradient vector flow (GVF) snakes, modified by an edge detection and snake-shifting step. Following this, a 3D model is constructed. We then estimate the volume of the airway based on segmented 3D shape.
authors.affiliation: NSERC Research Fellow, Computer and Information Sciences Department, University of Pennsylvania, PA, USA. chenglin@seas.upenn.edu
authors.forename: Irene
authors.initials: I
authors.lastname: Cheng
authors.forename: Sharmin
authors.initials: S
authors.lastname: Nilufar
authors.forename: Carlos
authors.initials: C
authors.lastname: Flores-Mir
authors.forename: Anup
authors.initials: A
authors.lastname: Basu
mesh_terms: D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D012137:Respiratory System / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed