李振立，杨晓梅

四川大学电气信息学院，四川省成都市  610065

李振立★，男，1986年生，辽宁省沈阳市人，汉族，四川大学在读硕士，主要从事数字图像处理方面的研究。
lzl.scu.sy@163. com

通讯作者：杨晓梅，博士，副教授，硕士生导师，四川大学电气信息学院自动化系，四川省成都市 610065

Tagged cardiac MR image segmentation based on texture analysis

Li Zhen-li, Yang Xiao-mei

School of Electrical Engineering and Information, Sichuan University, Chengdu  610065, Sichuan Province, China

Li Zhen-li★, Studying for master’s degree, School of Electrical Engineering and Information, Sichuan University, Chengdu  610065, Sichuan Province, China
lzl.scu.sy@163.com

Correspondence to: Yang Xiao-mei, Doctor, Associate professor, Master’s supervisor, School of Electrical Engineering and Information, Sichuan University, Chengdu  610065, Sichuan Province, China

Abstract

BACKGROUND: Analysis of the left ventricle motion and deformation is based on accurate segmentation of the left ventricle boundaries. However, affected by the strong gradient from tagged lines in tagged cardiac MR images, extracting endocardium boundaries makes itself very difficult.
OBJECTIVE: A new texture analysis method is proposed, based on a minimum-variance energy map, to suppress the effect of tag lines on image segmentation.
METHODS: Firstly, weighted sums of the local minimum and variance were computed, generating a minimum-variance map; Secondly, some block-like artifacts in the map were filtered off, as well as the boundaries were preserved by using median filter; Finally, GVF-snake model was applied to detect the endocardial contour.
RESULTS AND CONCLUSION: According to the distribution characteristics of tag lines in tagged cardiac MR images, a new texture analysis method based on a minimum-variance energy map is proposed, which can effectively remove tag lines. Experimental results proved that the application of GVF-snake model in the energy map generated by the proposed method can well extract the endocardium boundary of the left ventricle in tagged cardiac MR image.

摘要

背景：左心室边界的准确分割是对左心室运动及形变进行分析的前提。由于受带标记线心脏核磁共振图像中标记线强梯度的影响，对左心室内膜的提取变得非常困难。
目的：为了抑制标记线对图像分割的影响，提出了一种基于最小值-方差能量图的纹理分析方法。
方法：首先对局部最小值和方差进行加权求和，得到能量图；然后利用中值滤波滤除能量图中的伪影并保持边界；最后，应用GVF-snake模型提取左心室内膜。
结果与结论：针对标记线在心脏MR图像中的分布特征，提出了一种基于最小值-方差的纹理分析方法，该方法有效地去除了标记线。结果提示，对使用该纹理分析方法生成的能量图应用GVF-snake模型可以较好地提取左心室内膜。
关键词：心脏核磁共振图像；纹理分析；左心室；标记线；GVF-snake模型
doi:10.3969/j.issn.1673-8225.2011.09.001

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