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Interactive Cardiac Image Analysis for Biventricular Function of the Human Heart

机译:心脏的双心室功能的交互式心脏图像分析。

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We developed an interactive tool for biventricular function analysis from cardiac magnetic resonance (MR) images based on the guide point modelling (GPM) approach [1], First we built a deformable model of both ventricles of the human heart which consisted of 138 nodes and 82 hexahedral elements, each with bicubic-Bezier-linear interpolation. The model was fitted to a digitized human data set for use as the prior shape in the GPM scheme, which we modified to have a 'predictor' step that used a host mesh fitting algorithm [2] to generate predicted points (PPs) based on the user-defined guide points (GPs). Then the model was fitted towards both GPs and PPs through linear least square minimization. The inclusion of the PPs significantly improved the numerical stability of the linear least square fit and significantly accelerated the solution time. This methodology requires further validation for future application in clinical biventricular analysis.
机译:我们基于指导点建模(GPM)方法[1],开发了一种用于从心脏磁共振(MR)图像进行双心室功能分析的交互式工具。首先,我们建立了由138个结点组成的人心脏两个心室的可变形模型。 82个六面体元素,每个元素具有双三次贝塞尔线性插值。该模型适合数字化的人类数据集,以用作GPM方案中的先前形状,我们对其进行了修改,使其具有一个“预测器”步骤,该步骤使用主机网格拟合算法[2]根据以下内容生成预测点(PP):用户定义的指导点(GP)。然后,通过线性最小二乘最小化将模型拟合到GP和PP。 PP的加入显着改善了线性最小二乘拟合的数值稳定性,并显着加快了求解时间。此方法需要进一步验证,以供将来在临床双心室分析中应用。

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