Airway Segmentation and Measurement in CT Images

Author

Cheng, I-Chun ; Nilufar, S. ; Flores-Mir, C. ; Basu, A.

Author_Institution

Univ. of Pennsylvania, Philadelphia

fYear

2007

fDate

22-26 Aug. 2007

Firstpage

795

Lastpage

799

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.

Keywords

biomedical measurement; computerised tomography; edge detection; filtering theory; gradient methods; heuristic programming; image segmentation; lung; medical image processing; pneumodynamics; volume measurement; 3D airway segmentation; airway volume measurement; automatic seed region detection; cone beam CT images; edge detection; gradient vector flow snakes; heuristic algorithm; morphological filtering; snake-shifting step; Biomedical imaging; Computed tomography; Gravity; Gray-scale; Image reconstruction; Image registration; Image segmentation; Lungs; Magnetic resonance imaging; Robustness; Humans; Imaging, Three-Dimensional; Respiratory System; Tomography, X-Ray Computed;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE

Conference_Location

Lyon

ISSN

1557-170X

Print_ISBN

978-1-4244-0787-3

Type

conf

DOI

10.1109/IEMBS.2007.4352410

Filename

4352410