title: Dynamic directional gradient vector flow for snakes.
abstract: Snakes, or active contour models, have been widely used in image segmentation. However, most present snake models do not discern between positive and negative step edges. In this paper, a new type of dynamic external force for snakes named dynamic directional gradient vector flow (DDGVF) is proposed that uses this information for better performance. It makes use of the gradients in both x and y directions and deals with the external force field for the two directions separately. In snake deformation, the DDGVF field is utilized dynamically according to the orientation of snake in each iteration. Experimental results demonstrate that the DDGVF snake provides a much better segmentation than GVF snake in situations when edges of different directions are present which pose confusion for segmentation.
authors.affiliation: School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. jpcheng@pmail.ntu.edu.sg
authors.forename: Jierong
authors.initials: J
authors.lastname: Cheng
authors.forename: Say Wei
authors.initials: SW
authors.lastname: Foo
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity