Intrathoracic Airway Tree Segmentation from CT Images Using a Fuzzy Connectivity Method

Yousefi Rizi, Fereshteh; Ahmadian, Alireza; FatemiZadeh, Emad; Alirezaie, Javad; Rezaie, Nader

doi:10.22038/ijmp.2009.7392

Intrathoracic Airway Tree Segmentation from CT Images Using a Fuzzy Connectivity Method

Document Type : Original Paper

Authors

Fereshteh Yousefi Rizi ¹

Alireza Ahmadian ²

Emad FatemiZadeh ³

Javad Alirezaie ⁴

Nader Rezaie ⁵

¹ Master of Science in Biomedical Engineering, Department of Biomedical Systems & Medical Physics, Tehran University of Medical Sciences

² 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.

³ Assistant Professor in Biomedical Engineering, Electrical Engineering Dept., Sharif University of Technology, Tehran, Iran.

⁴ Associate Professor in Biomedical Engineering, Electrical Engineering Dept., Ryerson University, Toronto, Canada.

⁵ Assistant Professor, Pneumologist Consultant, Iran University of Medical Sciences, Internal Medicine Group, Tehran, Iran.

10.22038/ijmp.2009.7392

Abstract

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.

Keywords

Airway tree segmentation

Fuzzy connectivity

Fuzzy C-Mean

Subjects