Airway segmentation and measurement in CT images.
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.
Cheng
Irene
I
NSERC Research Fellow, Computer and Information Sciences Department, University of Pennsylvania, PA, USA. chenglin@seas.upenn.edu
Nilufar
Sharmin
S
Flores-Mir
Carlos
C
Basu
Anup
A
D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D012137:Respiratory System / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed