title: [Self-adapted segmentation of pulmonary nodule based on region growing].
abstract: 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.
authors.affiliation: Biomedical Engineering School, Southern Medical University, Guangzhou 510515, China. caolei@fimmu.com
authors.forename: Lei
authors.initials: L
authors.lastname: Cao
authors.forename: Li-jun
authors.initials: LJ
authors.lastname: Lu
authors.forename: Rui-meng
authors.initials: RM
authors.lastname: Yang
authors.forename: Wu-fan
authors.initials: WF
authors.lastname: Chen
mesh_terms: 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