Active Contour Model Coupling with Higher Order Diffusion for Medical Image Segmentation. (2nd March 2014)

• Record Type: Journal Article
• Authors: Wang, Guodong; Xu, Jie; Dong, Qian; Pan, Zhenkuan
• Other Names: Wei Guowei Academic Editor.
• Is Part Of: International journal of biomedical imaging. Volume 2014(2014)
• Publication Date: 2014-03-02
• Subjects: Diagnostic imaging -- Periodicals; Imaging systems in medicine -- Periodicals; Imagerie pour le diagnostic; Imagerie médicale; Diagnostic imaging; Imaging systems in medicine; Diagnostic Imaging -- Periodicals; Electronic journals; Periodicals; 616.0754
• DOI: 10.1155/2014/237648
• Languages: English
• ISSNs: 1687-4188

Abstract

Abstract : Active contour models are very popular in image segmentation. Different features such as mean gray and variance are selected for different purpose. But for image with intensity inhomogeneities, there are no features for segmentation using the active contour model. The images with intensity inhomogeneities often occurred in real world especially in medical images. To deal with the difficulties raised in image segmentation with intensity inhomogeneities, a new active contour model with higher-order diffusion method is proposed. With the addition of gradient and Laplace information, the active contour model can converge to the edge of the image even with the intensity inhomogeneities. Because of the introduction of Laplace information, the difference scheme becomes more difficult. To enhance the efficiency of the segmentation, the fast Split Bregman algorithm is designed for the segmentation implementation. The performance of our method is demonstrated through numerical experiments of some medical image segmentations with intensity inhomogeneities.