An efficient method of automatic pulmonary parenchyma segmentation in CT images.
Based on special distributing characteristics of pixel intensity in lung CT images, an efficient lung segmentation method is introduced. Associating approach of image threshold with fast region flood filling technique, this method can extract pulmonary parenchyma from CT images simply. After a preprocessing step for noise removal, it segments the lung CT image slice utilizing a threshold method at first, and then applies a fast and simple method to finish flood filling of the non-lung area. In the following steps, the lung area can be extracted automatically after an erosion operation and an area-filtering step. The presented experiment results have proved its validity.
Chen
Zhaoxue
Z
College of Medical Instrumentation & Foodstuff, University of Shanghai for Science and Technology, Shanghai, 200093, China. chenzhaoxue@163.com
Sun
Xiwen
X
Nie
Shengdong
S
D000465:Algorithms; D001185:Artificial Intelligence; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods; D008168:Lung / Q000000981:diagnostic imaging*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*