摘要
提出了一种基于局部灰度聚类(LIC)模型和分水岭算法的心脏核磁共振成像(MRI)图像左心室底层组织分割方法.首先,使用LIC模型对图像进行初步分割,提取出图像中的组织和器官;然后,使用分水岭算法弥补粘连的不同组织或器官之间缺失的边界,将其分开,人工选取种子点进行区域生长初步提取左心室;最后,利用左心室形状特征的先验知识判断提取的左心室中是否包含主动脉,若包含则去除主动脉,得到精确的左心室分割结果.实验结果表明,该方法能有效去除心脏MRI图像上左心室底层存在的弱边界和边缘泄露的影响,得到准确的左心室底层组织分割结果.
A novel method was proposed for segmenting the base of the left ventricle in cardiac magnetic resonance imaging （MRI） images based on local intensity clustering （LIC） model and watershed algorithm. First,the cardiac MRI images were segmented by LIC model to detect the tissues and organs. Then,the connected tissues and organs were separated by using watershed algorithm to make up for the missing edges. The seed points were artificially selected to carry growing for the preliminary extraction of left ventricle. Finally,whether the preliminary extraction of the left ventricle contains the aorta will be judged by priori knowledge of the shape features of the left ventricle,if the preliminary extraction of the left ventricle contain the aorta,the effect of the missing edge caused by the aorta will be removed to get an accurate segmentation result of the base of left ventricular. Experimental results demonstrated that the proposed method can effectively remove the effect of weak edges and edge leakage of the base of the left ventricle in MRI images to obtain an accurate segmentation result of the base of left ventricular.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2017年第10期1383-1387,共5页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目(61374015
61202258
61302012)
教育部高等学校博士学科点专项科研基金资助项目(20110042120037)
中央高校基本科研业务费探索导向重点项目(N110219001)
辽宁省自然科学基金资助项目(201102067)
关键词
心脏核磁共振图像
左心室
图像分割方法
LIC模型
分水岭算法
cardiac magnetic resonance images
left ventricle
image segmentation method
LIC model
watershed algorithm
