吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (5): 1688-1696.doi: 10.13229/j.cnki.jdxbgxb201605045
王品1, 何璇1, 吕洋1, 李勇明1,2, 邱明国2, 刘书君1
WANG Pin1, HE Xuan1, LYU Yang1, LI Yong-ming1,2, QIU Ming-guo2, LIU Shu-jun1
摘要: 为了从膝关节磁共振图像(MRI)中分割出膝软骨,提出一种基于多特征支持向量机(SVM)边缘定位和弹性区域生长的自动分割算法。首先,采用自适应Canny边缘检测算法提取图像主要边缘;再对边缘提取多个图像特征,结合SVM算法对边缘进行分类,完成软骨边缘定位;然后,在软骨边缘的基础上进行种子点及软骨像素区域的选择;之后基于选择的结果采用弹性区域生长进行初步软骨分割;最后,基于先验知识和形态学获得最终膝软骨分割结果。实验结果表明:该算法能够准确、快速地自动分割出膝关节MRI中不同的膝软骨,其中股软骨、胫软骨、髌软骨的平均评价重要指标(DSC)分别可达0.8543、0.8280、0.8703,与手工分割结果具有较高的一致性。
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