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 multiseeded fuzzy based region growing approach in conjuction 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.
Airway tree segmentation fuzzy region growing spatial information
Fereshteh Yousefi Rizi Alireza Ahmadian Nima Sahba Vahid Tavakoli Javad Alirezaie Emad Fatemizadeh Nader Rezaie
Dept. Biomedical Engineering, Medical science/University of Tehran & Research Center for science and Dept. Electrical Engineering, Ryerson University Toronto, Canada Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran Pneumologist Consultant, Iran University of Medical Sciences, Firoozgar Hospital, Tehran, Iran
国际会议
上海
英文
2295-2298
2008-05-16（万方平台首次上网日期，不代表论文的发表时间）