Airway segmentation and measurement in CT images

Irene Cheng; Sharmin Nilufar; Carlos Flores-Mir; Anup Basu

doi:10.1109/IEMBS.2007.4352410

Airway segmentation and measurement in CT images

Annu Int Conf IEEE Eng Med Biol Soc. 2007:2007:795-9. doi: 10.1109/IEMBS.2007.4352410.

Authors

Irene Cheng¹, Sharmin Nilufar, Carlos Flores-Mir, Anup Basu

Affiliation

¹ NSERC Research Fellow, Computer and Information Sciences Department, University of Pennsylvania, PA, USA. chenglin@seas.upenn.edu

PMID: 18002076
DOI: 10.1109/IEMBS.2007.4352410

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.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Humans
Imaging, Three-Dimensional / methods*
Respiratory System / diagnostic imaging*
Tomography, X-Ray Computed*