A Hybrid Fuzzy Based Algorithm for 3D Human Airway Segmentation

Segmentation of the human airway tree from volumetric computed tomography images is an important stage for many clinical applications such as virtual bronchoscopy. The main challenges of previously developed methods are to deal with two problems namely, leaking into the surrounding lung parenchyma during segmentation and the need to manually adjust the parameters. To overcome these problems, a multi- seeded fuzzy based region growing approach in conjunction with the spatial information of voxels is proposed. Comparison with a commonly used region growing segmentation algorithm shows that the proposed method retrieves more accurate results by achieving the specificity and sensitivity of 98.81% and 85.18%, respectively. The proposed algorithm needs no manually adjustment of parameters as well as any pre-filtering process, while leading to deliver the clinically accepted segmentation result with no leakage.