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2-D segmentation of left ventricle in magnetic resonance images based on an optical flow algorithm

机译:基于光流算法的磁共振图像左心室二维分割

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The optical flow enables the accurate estimation of cardiac motion. In this research, this tool is exploited to obtain the 2-D segmentation of the left ventricle in a cardiac sequence of magnetic resonance images. The proposed technique consists in taking a manually extracted left ventricle contour corresponding to an instant of the cardiac sequence. Then, the Left Ventricle contour for the next time instant is estimated based on calculation of the optical flow using the Horn and Schunck algorithm. The method is validated using two synthetic image sequences whose velocity field is known. Then, the technique is applied to a 3D magnetic resonance image sequence and it is validated by performing the comparison with respect to the manual segmentation using the Dice coefficient. The results show that the segmentation near the base, the equator and the apex have a Dice coefficient higher than 84%.
机译:光流使得能够准确估计心脏运动。在这项研究中,利用该工具在磁共振图像的心脏序列中获得左心室的二维分割。所提出的技术在于获取对应于心脏序列瞬间的手动提取的左心室轮廓。然后,基于使用Horn和Schunck算法的光流计算,估计下一个时刻的左心室轮廓。使用两个速度场已知的合成图像序列验证了该方法。然后,将该技术应用于3D磁共振图像序列,并通过使用Dice系数对手动分割进行比较来验证该技术。结果表明,在基部,赤道和顶点附近的分割具有高于84%的Dice系数。

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