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Tracking Left Ventricular Borders in 3D EchocardiographicSequences using Motion-Guided Optical Flow

机译:使用运动引导光流跟踪3D超声心动图中的左心室边框

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For obtaining quantitative and objective functional parameters from three-dimensional (3D) echocardiographic sequences, automated segmentation methods may be preferable to cumbersome manual delineation of 3D borders. In this study, a novel optical-flow based tracking method is proposed for propagating 3D endocardial contours of the left ventricle throughout the, cardiac cycle. To take full advantage of the time-continuous nature of cardiac motion, a statistical motion model was explicitly embedded in the optical flow solution. The cardiac motion was modeled as frame-to-frame affine transforms, which were extracted using Procrustes analysis on a set of training contours. Principal component analysis was applied to obtain a compact model of cardiac motion throughout the whole cardiac cycle. The parameters of this model were resolved in an optical flow manner, via spatial and temporal gradients in image intensity. The algorithm was tested on 36 noncontrast and 28 contrast enhanced 3D echocardiographic sequences in a leave-one-out manner. Good results were obtained using a combination of the proposed motion-guided method and a purely data-driven optical flow approach. The improvement was particularly noticeable in areas where the LV wall was obscured by image artifacts. In conclusion, the results show the applicability of the proposed method in clinical quality echocardiograms.
机译:用于从三维(3D)超声心动图的序列,获得定量和客观的功能参数自动分割的方法可以是优选的三维边界的麻烦的手动圈定。在这项研究中,一种新颖的光流,提出了在整个心脏周期传播3D左心室心内膜轮廓基于跟踪方法。为了充分利用的心脏运动的时间连续性质,统计运动模型被明确嵌入在光流解决方案。的心脏运动建模为帧到帧的仿射变换,其中使用普鲁克分析一组训练轮廓的提取。主成分分析应用于获得在整个心动周期的心脏的运动的紧凑模型。该模型的参数中的光流的方式解决,通过在图像强度的空间和时间梯度。该算法是在留一出的方式对36非增强和28对比增强三维超声心动图的序列进行测试。使用所提出的运动引导方法的组合和一个纯粹的数据驱动的光流的方法得到了良好的结果。的改进是在将LV壁是由图像伪影遮蔽的区域尤其明显。总之,结果表明,临床质量超声心动图所提出的方法的适用性。

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