An Efficient Modified Level Set Method For Brain Tissue Segmentation

摘要：

The paper presents a new efficient method for brain tissue extraction. Firstly, the speed of segmentation is enhanced through improving classical distance matrix. It can accelerate the distance function convergence faster, and the accuracy is not reduced simultaneously. Secondly, the uniqueness of classical result is changed through the improved method. The evolving lines will be stopped at the same level gray, so the primal fluid can be wiped off. White matter and gray matter are extracted more accurate. Finally, a dynamic condition for ending iteration is presented through comparing the interval frames. The improvement changes the flaw of setting evolving times to end iteration, so it can make the veracity and speed much better. The methods are generally applied to image 2D and 3D segmentation, and the results of experiment indicate that the improvements can make the brain tissue extraction more rapid and accurate, and will be very helpful for doctor to make a definite diagnosis.

关键词： brain tissue extraction level set C-V model regions merging

作者: Jia Di Yang Jin-Zhu Zhang Yi-Fei

作者单位: Key Laboratory of Medical Image Computing of Ministry of Educaion Northeast University ShenYang 110179,China

会议类型: 国际会议

会议名称: 2010 IEEE信息与自动化国际会议(ICIA 2010)

会议地点: 哈尔滨

会议语种:英文

页码: 1-5

在线出版日期: 2010-06-20（万方平台首次上网日期，不代表论文的发表时间）