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.
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