Segmentation of Salivary Gland Tumors in Ultrasonic Images Based on Anisotropic Diffusion and Random Walk

摘要：

　　Aimed at the difficult segmentation of ultrasonic tumor image with strong speckle noise,low contrast and weak boundaries,a novel method for segmentation of ultrasonic image is proposed.In order to suppress speckle noise and enhance the edge details,the anisotropic diffusion algorithm combined with the Laplacian operator is introduced into ultrasound images,of which the operator is able to discriminate the gray changes caused by noise or the edge.Then the random walk model in graph theory is employed to achieve an effective segmentation.Lots of clinical ultrasound images of salivary gland tumor are tested and the experiment results demonstrate that the proposed method possesses the nice properties of anisotropic diffusion algorithm and random walk algorithm,overcoming prone over-segmentation or under-segmentation in traditional random walk.In addition,the method bears a high calculating speed and segments tumor accurately and effectively.

关键词： ultrasonic image segmentation random walk anisotropic diffusion salivary gland tumors speckle noise

作者: SU Hai-nan CHEN Hou-jin LI Ju-peng LI Yan-feng

作者单位: School of Electronic and Information Engineering, Beijing Jiaotong University ,Beijing,China

会议类型: 国际会议

会议名称: 2012 IEEE 11th International Conference on Signal Processing (第11届IEEE信号处理国际会议)

会议地点: 北京

会议语种:英文

页码: 677-680

在线出版日期: 2012-10-21（万方平台首次上网日期，不代表论文的发表时间）