Contour extraction of medical images using improved deformable model by integrating region information
Traditional deformable models provide a global method for image analysis, but these is easily relapsed into a local optimal in a high noise image and invalid for the image contour with deeply narrow concavities. In this paper, we proposed a novel deformable model to extract the contour of interested object in medical images in medical images. In the procedure of the evolvement of contour curve, by introducing the designed image transform operator to derive the region force from the region information included in the interested object, our method could improve the capacity to alleviate the sensitivity to image noise and converge into complex boundary. Experiments were performed with synthetic and medical images and the feasibility and robustness of our method was demonstrated.
Contour extraction deformable model region information
Yang-Guang Sun Guang-Yue Hei Jiang-Qing Wang Ming-Yue Ding
College of Computer Science, South-Central University for Nationalities, Wuhan 430074, China “Image College of Computer Science, South-Central University for Nationalities, Wuhan 430074, China College of Life Science and Technology, HUST, Wuhan 430074, China “Image Processing and Intelligence
国际会议
桂林
英文
1-6
2011-11-01（万方平台首次上网日期，不代表论文的发表时间）