The Tracking Framework for Lobe Fissure Based on the Modified Ant Colony Optimization Algorithm

The chest computed tomography (CT) is the most commonly used imaging technique for the inspection of lung lesions. In order to provide the physician more valuable preoperative opinions, a powerful computer-aided diagnostic (CAD) system is indispensable. In this paper, we aim to develop an efficient tracking framework to extract the lobe fissures by the proposed modified ant colony optimization (ACO) algorithm. In this procedure, we will increase the consistency of pheromones on the lobe fissure. Hence, the gray-value of lobe fissure will be improved, and it may promote the accuracy of segmentation procedure. In order to validate the proposed system, we have tested our method in a database from 15 lung patients. The experiments indicate our method results more satisfied performance in most cases, and can help investigators detect lung lesion for further examination.