Automated extraction of bronchus from 3D CT images of lung based on genetic algorithm and 3D region growing

Abstract

In this paper, we propose a method to automate the segmentation of airway tree structures in lung from a stack of gray-scale computed tomography (CT) images. A three- dimensional seeded region growing is performed on images without any preprocessing operation to obtain the segmented bronchus area. We first apply genetic algorithm (GA) to retrieve the seed point and it is based on the geometric features (shape, location and size) of the airway tree. By the feature of the size of the lung and airway tree, an optimal threshold value is obtained. The final extracted bronchus area with the optimal threshold value is reconstructed and visualized by 3D texture mapping method.