首页> 外文会议>Physiology, Function, and Structure from Medical Images pt.1; Progress in Biomedical Optics and Imaging; vol.6,no.23 >Lagrangian and Eulerian Biventricular Strains from Anatomical NURBS Models Using Tagged MRI
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Lagrangian and Eulerian Biventricular Strains from Anatomical NURBS Models Using Tagged MRI

机译:使用标记的MRI从解剖NURBS模型中的拉格朗日和欧拉双心室菌株

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We present current research in which both left and right ventricular deformation is estimated from tagged cardiac magnetic resonance imaging using volumetric deformable models constructed from nonuniform rat ional B-splines (NURBS). The four model types considered include Cartesian-based NURBS models with both a cylindrical and prolate-spheroidal parameterization, prolate spheroidal-based NURBS models with a prolate-spheroidal parameterization, and cylindrical-based NURBS models with a cylindrical parameterization. For each frame subsequent to end-diastole, a NURBS model is constructed by fitting two surfaces with the same parameterization to the corresponding set of epicardial and endocardial contours from which a volumetric model is created. Using normal displacements of the three sets of orthogonal tag planes as well as displacements of contour/tag line intersection points and tag plane intersection points, one can solve for the optimal homogeneous coordinates, in a weighted least squares sense, of the control points of the deformed NURBS model at end-diastole using quadratic programming. This allows for subsequent forward displacement fitting from end-diastole to all later time frames. After fitting to all time points of data, lofting the NURBS model at each time point creates a comprehensive 4-D NURBS model. From this model, we can extract 3-D myocardial deformation fields and corresponding strain maps which are local measures of non-rigid deformation. The results show that, in the case of simulated data, the quadratic Cartesian-based NURBS model outperformed its counterparts in predicting normal strain. This model was used to then calculate normal Lagrangian and Eulerian strains in canine data.
机译:我们目前的研究中,左心室和右心室的变形都是根据使用不均匀比例B样条曲线(NURBS)构建的体积可变形模型通过标记的心脏磁共振成像估计出来的。考虑的四种模型类型包括同时具有圆柱体和长椭球形参数化的基于笛卡尔的NURBS模型,具有圆柱体椭球状参数化的基于椭球的NURBS模型以及具有圆柱体参数化的基于圆柱体的NURBS模型。对于舒张末期后的每一帧,通过将具有相同参数化的两个曲面拟合到相应的心外膜和心内膜轮廓集上来构建NURBS模型,从中创建一个体积模型。使用三组正交标签平面的法向位移以及轮廓/标签线相交点和标签平面相交点的位移,可以在加权最小二乘意义上求解最优控制点的均质坐标。使用二次规划在舒张末期变形NURBS模型。这允许从舒张末期到所有随后的时间范围的后续向前位移拟合。拟合所有数据时间点后,在每个时间点放样NURBS模型将创建一个全面的4-D NURBS模型。从该模型中,我们可以提取3-D心肌变形场和相应的应变图,这些图是非刚性变形的局部量度。结果表明,在模拟数据的情况下,基于笛卡尔直角坐标系的二次NURBS模型在预测正常应变方面优于同类模型。然后使用该模型来计算犬类数据中的正常拉格朗日和欧拉菌株。

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