intrathoracic airway tree segmentation from ct images using a fuzzy connectivity method

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.