Fereshteh Yousefi Rizi - Master of Science in Biomedical Engineering, Department of Biomedical Systems & Medical Physics, Tehran University of Medical Sciences
Alireza Ahmadian - Associate Professor in Biomedical Engineering, Biomedical Systems & Medical Physics Dept., Tehran University of Medical Sciences & Research Center for Science and Technology in Medicine, Tehran, Iran.
Emad FatemiZadeh - Assistant Professor in Biomedical Engineering, Electrical Engineering Dept., Sharif University of Technology, Tehran, Iran.
Javad Alirezaie - Associate Professor in Biomedical Engineering, Electrical Engineering Dept., Ryerson University, Toronto, Canada.

Introduction: Virtual bronchoscopy is a reliable and efficient diagnostic method for primary symptoms of lung cancer. The segmentation of airways from CT images is a critical step for numerous virtual bronchoscopy applications. Materials and Methods: To overcome the limitations of the fuzzy connectedness method, the proposed technique, called fuzzy connectivity - fuzzy C-mean (FC-FCM), utilized the FCM algorithm. Then, hanging-togetherness of pixels was handled by employing a spatial membership function. Another problem in airway segmentation that had to be overcome was the leakage into the extra-luminal regions due to the thinness of the airway walls during the process of segmentation. Results:   The result shows an accuracy of 92.92% obtained for segmentation of the airway tree up to the fourth generation. Conclusion:  We have presented a new segmentation method that is not only robust regarding the leakage problem but also functions more efficiently than the traditional FC method. 

Airway tree segmentation, Fuzzy connectivity, Fuzzy C-Mean