title: [Medical image segmentation based on Gibbs morphological gradient and distance map Snake model].
abstract: OBJECTIVE
  To propose a new algorithm for medical image segmentation based on Gibbs morphological gradient and distance map (DM) Snake model, which allows identification of the correct contours of the objects when processing medical images with noises and pseudo-edges.
  
  
  METHODS
  Gibbs morphological gradient was deduced and the method for image segmentation based on Gibbs morphological gradient and distance map Snake model was presented.
  
  
  RESULTS
  This new medical image segmentation algorithm proved to effectively suppress the noises and pseudo-edges when calculating distance map.
  
  
  CONCLUSIONS
  The proposed algorithm is robust for image noise suppression and allows easy implementation in clinical image segmentation without the need of user interventions.
authors.affiliation: School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China. redhorn@tom.com
authors.forename: Guang-Bin
authors.initials: GB
authors.lastname: Cheng
authors.forename: Li-Wei
authors.initials: LW
authors.lastname: Hao
authors.forename: Wu-Fan
authors.initials: WF
authors.lastname: Chen
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D017143:Fuzzy Logic; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed