Lung detection using Adaptive Border correction

Juxta-pleural is one of the lung nodules types that attached to the chest wall and has the same intensity. The presence of this type of nodules can be a mistake in lung segmentation. We propose a method for lung segmentation with bidirectional peak detection method that gives the result of lung border to be a solution to the problem. The method we propose has been tested with 140 3D CT images from ILDC-IDRI dataset which only contains juxta-pleural and juxta-vascular nodules, result shows only 14.3% of under-segmentation. We have compared with another two methods which are Morphological Closing and Adaptive Border Marching (ABM). The proposed method achieved the fastest computation level at 0.18 sec/slice or three times faster than the speed of morphological methods (0.56 sec/slice) and 40 times faster than the speed of ABM method (7.12 sec/slice). The propose method has potential to be implemented in embedded systems.