首页> 外文会议> >Cardiac Motion Estimation from Gated Emission Computed Tomography Images
【24h】

Cardiac Motion Estimation from Gated Emission Computed Tomography Images

机译:门控发射计算机断层扫描图像的心脏运动估计

获取原文
获取外文期刊封面目录资料

摘要

Quantitative description of the cardiac left ventricle (LV) motion is desirable to assist in detecting myocardial motion abnormalities. It has been recognized that the torsion component of the LV movement is considerably more difficult to track than its radial counterpart. We develop a motion estimation method that estimates three-dimensional (3-D) LV motion vector field (MVF) that includes the twisting motion from four-dimensional (4-D) gated myocardial perfusion (MP) emission computed tomography (ECT) images. The method is implemented through searching for an MVF that minimizes a cost function consisting of the image matching error between two frames and the weighted strain energy constraint that prevents physically implausible movement. The strain energy is calculated on segmented heart voxels with physical parameters that model the material properties of the myocardium. The close-to-optimal weight of the strain energy was obtained by minimizing the root-mean-square errors of the estimated MVF from standard NCAT phantom images simulating gated MP data. The performance of this method has been quantitatively evaluated, in estimating MVF from NCAT generated images with specified motion corresponding to varied LV twisting angles (different from the standard phantom) and to regional LV motion defects. The estimated defect MVF can be distinguished from the estimated normal MVF.
机译:需要对心脏左心室(LV)运动进行定量描述,以帮助检测心肌运动异常。已经认识到,LV运动的扭转分量比其径向对应物更难追踪。我们开发了一种运动估计方法,该方法可以估计三维(3-D)LV运动矢量场(MVF),其中包括来自二维(4-D)门控心肌灌注(MP)发射计算机断层扫描(ECT)图像的扭曲运动。该方法是通过搜索使成本函数最小化的MVF来实现的,该函数包括两个帧之间的图像匹配误差以及加权的应变能约束,可防止物理上不合理的运动。应变能是在分段的心脏体素上计算的,其物理参数可对心肌的材料属性进行建模。通过最小化模拟门控MP数据的标准NCAT幻像估计的MVF的均方根误差,获得了接近最佳的应变能权重。在从NCAT生成的图像中估计MVF时,已对该方法的性能进行了定量评估,该图像的指定运动对应于不同的LV扭曲角度(不同于标准体模)和局部LV运动缺陷。可以将估计的缺陷MVF与估计的正常MVF区分开。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号