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Segmentation of the Left Ventricle Using Active Contour Method with Gradient Vector Flow Forces in Short-Axis MRI

机译:使用带有梯度矢量流量的活动轮廓方法在短轴MRI中分割左心室的分割

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In this paper a left ventricle segmentation approach in short-axis MRI is proposed. It is based on an active contour method and gradient vector flow field forces. Firstly, algorithm delineates endocardium using active contour method approach assisted by gradient vector flow field forces. After that, the epicardium is outlined by proposed divergence rays method and corrected by Fourier descriptors to smoothen an epicardium curve. An algorithm has been tested on eight healthy patients and compared to a manual delineation of endo- and epicardium boundaries. Validity of an algorithm is checked by linear regression analysis, correlation coefficients, and RSME errors. Sample Pearson product-moment correlation coefficients between automatic and manual delineation are r_(ENDO) = 0.95 and r_(EPI) = 0.86. The coefficients of determination and RMSEs are R_(ENDO)~2 = 0.9, R_(EPI)~2 = 0.74 and RMSE_(ENDO) = 5.303 ml, RMSE_(EPI) = 21.973 ml, respectively. These experiments confirm accuracy and robustness of the proposed approach.
机译:本文提出了短轴MRI中的左心室分割方法。它基于主动轮廓方法和梯度矢量流场力。首先,算法利用梯度向量流场力辅助的主动轮廓方法方法描绘心内膜内膜。之后,通过提出的分歧射线方法概述了外膜,并由傅立叶描述符校正以使表皮曲线平滑。在八名健康患者上测试了一种算法,并与手动描绘了内皮和表皮界的划分。通过线性回归分析,相关系数和RSME错误检查算法的有效性。 Sample Pearson Product-Moreast Sone的自动和手动描绘之间的相关系数是R_(ENDO)= 0.95和R_(EPI)= 0.86。测定系数和RMSE是R_(endo)〜2 = 0.9,R_(EPI)〜2 = 0.74和RMSE_(endo)= 5.303ml,RMSE_(EPI)= 21.973ml。这些实验确认了所提出的方法的准确性和稳健性。

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