Share Email Print
cover

Proceedings Paper

A volumetric pulmonary CT segmentation method with applications in emphysema assessment
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

A segmentation method is a mandatory pre-processing step in many automated or semi-automated analysis tasks such as region identification and densitometric analysis, or even for 3D visualization purposes. In this work we present a fully automated volumetric pulmonary segmentation algorithm based on intensity discrimination and morphologic procedures. Our method first identifies the trachea as well as primary bronchi and then the pulmonary region is identified by applying a threshold and morphologic operations. When both lungs are in contact, additional procedures are performed to obtain two separated lung volumes. To evaluate the performance of the method, we compared contours extracted from 3D lung surfaces with reference contours, using several figures of merit. Results show that the worst case generally occurs at the middle sections of high resolution CT exams, due the presence of aerial and vascular structures. Nevertheless, the average error is inferior to the average error associated with radiologist inter-observer variability, which suggests that our method produces lung contours similar to those drawn by radiologists. The information created by our segmentation algorithm is used by an identification and representation method in pulmonary emphysema that also classifies emphysema according to its severity degree. Two clinically proved thresholds are applied which identify regions with severe emphysema, and with highly severe emphysema. Based on this thresholding strategy, an application for volumetric emphysema assessment was developed offering new display paradigms concerning the visualization of classification results. This framework is easily extendable to accommodate other classifiers namely those related with texture based segmentation as it is often the case with interstitial diseases.

Paper Details

Date Published: 13 March 2006
PDF: 12 pages
Proc. SPIE 6143, Medical Imaging 2006: Physiology, Function, and Structure from Medical Images, 61432U (13 March 2006); doi: 10.1117/12.652622
Show Author Affiliations
José Silvestre Silva, Univ. of Aveiro (Portugal)
Univ. of Coimbra (Portugal)
Augusto Silva, Univ. of Aveiro (Portugal)
Instituto de Engenharia Electrónica e Telemática de Aveiro (Portugal)
Beatriz Sousa Santos, Univ. of Aveiro (Portugal)
Instituto de Engenharia Electrónica e Telemática de Aveiro (Portugal)


Published in SPIE Proceedings Vol. 6143:
Medical Imaging 2006: Physiology, Function, and Structure from Medical Images
Armando Manduca; Amir A. Amini, Editor(s)

© SPIE. Terms of Use
Back to Top