[Self-adapted segmentation of pulmonary nodule based on region growing].
OBJECTIVE
To improve the accuracy and efficiency of pulmonary nodule segmentation of thoracic CT image for computer-aided diagnostic (CAD) system, especially for those nodules adhering to the pleural or blood vessels.


METHODS
We proposed the automatic process of pulmonary nodule segmentation, and using region growing method based on the contrast and gradient, the pulmonary nodule images were acquired. A self-adapted morphologic segmentation algorithm was presented for the unsuccessful nodule segmentation using region growing.


CONCLUSIONS
Experiments on clinical 2D pulmonary images showed that the solitary pulmonary nodules and those adhering to the pleural or blood vessels could all be segmented. This pulmonary nodule segmentation algorithm is feasible for automated segmentation of the thoracic CT images.
Cao
Lei
L
Biomedical Engineering School, Southern Medical University, Guangzhou 510515, China. caolei@fimmu.com
Lu
Li-jun
LJ
Yang
Rui-meng
RM
Chen
Wu-fan
WF
D000465:Algorithms; D003936:Diagnosis, Computer-Assisted; D003937:Diagnosis, Differential; D006801:Humans; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed