[Medical image segmentation based on Gibbs morphological gradient and distance map Snake model].
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.
Cheng
Guang-Bin
GB
School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China. redhorn@tom.com
Hao
Li-Wei
LW
Chen
Wu-Fan
WF
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