Title :
Airway Segmentation and Measurement in CT Images
Author :
Cheng, I-Chun ; Nilufar, S. ; Flores-Mir, C. ; Basu, A.
Author_Institution :
Univ. of Pennsylvania, Philadelphia
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;
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
Print_ISBN :
978-1-4244-0787-3
DOI :
10.1109/IEMBS.2007.4352410
