The Lobe Fissure Tracking by the Modified Ant Colony Optimization Framework in CT Images

Algorithms

Chii-Jen Chen²  You-Wei Wang¹  Wei-Chih Shen⁴  Chih-Yi Chen³  Wen-Pinn Fang² 

[1] Department of Computer Science and Information Engineering, National Taiwan University, Taipei 10617, Taiwan; E-Mail:;Department of Computer Science and Information Engineering, Yuanpei University of Medical Technology, Hsinchu 30015, Taiwan; E-Mail:;Institute of Medicine, Chung Shan Medical University, Taichung 40201, Taiwan; E-Mail:;Department of Computer Science and Information Engineering, Asia University, Taichung 40402, Taiwan; E-Mail:

关键词: CT;    ant colony optimization algorithm;    lung;    lobe fissure;    segmentation;   

DOI  :  10.3390/a7040635

来源: mdpi

【 摘 要 】

Chest computed tomography (CT) is the most commonly used technique for the inspection of lung lesions. However, the lobe fissures in lung CT is still difficult to observe owing to its imaging structure. Therefore, in this paper, we aimed to develop an efficient tracking framework to extract the lobe fissures by the proposed modified ant colony optimization (ACO) algorithm. We used the method of increasing the consistency of pheromone on lobe fissure to improve the accuracy of path tracking. In order to validate the proposed system, we had tested our method in a database from 15 lung patients. In the experiment, the quantitative assessment shows that the proposed ACO method achieved the average F-measures of 80.9% and 82.84% in left and right lungs, respectively. The experiments indicate our method results more satisfied performance, and can help investigators detect lung lesion for further examination.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland.