Fuzzy Adaptive Level Set Algorithm for Brain Tissue Segmentation
This paper presents an image segmentation method based on fuzzy clustering and level set methods.The MRI image is firstly segmented with the fuzzy clustering method,and then the resulting fuzzy memberships are used to generate a new constraint function which guides the level-set curves evolution.Thanks to the new constraint term,the presented method is able to adaptively determine the directions of the curves evolution without any manual intervention.The new method does not depend excessively on the gradient information as the Geodesic Active Contour method does;therefore it is less sensitive to the noise.The region information provided by the first step of the algorithm allows to improve the segmentation accuracy of the brain tissues.The experimental quantitative and qualitative analyses indicate the capability of the proposed method to segment the brain tissues with high accuracy comparing with the fuzzy clustering method.
Zhibin Chen Tianshuang Qiu Su Ruan
Department of Electronic Engineering Dalian University of Technology 116024 Dalian,China;School of E Department of Electronic Engineering Dalian University of Technology 116024 Dalian,China CReSTIC,IUT de Troyes Universite de Reims Champagne-Ardenne 10026 Troyes Cedex,France
国际会议
9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)
北京
英文
2008-10-26（万方平台首次上网日期，不代表论文的发表时间）