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Barycentric Subspace Analysis: A New Symmetric Group-Wise Paradigm for Cardiac Motion Tracking

机译:重心子空间分析:心脏运动跟踪的一种新的对称群智范式

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In this paper, we propose a novel approach to study cardiac motion in 4D image sequences. Whereas traditional approaches rely on the registration of the whole sequence with respect to the first frame usually corresponding to the end-diastole (ED) image, we define a more generic basis using the barycentric subspace spanned by a number of references images of the sequence. These subspaces are implicitly defined as the locus of points which are weighted Karcher means of k + 1 references images. We build such subspace on the cardiac motion images, to get a Barycentric Template that is no longer defined by a single image but parametrized by coefficients: the barycentric coordinates. We first show that the barycentric coordinates - the coefficients of the projection of the motion during a cardiac sequence - define a meaningful signature for group-wise analysis of dynamics and can efficiently separate two populations. Then, we use the barycentric template as a prior for reg-ularization in cardiac motion tracking, efficiently reducing the error of tracking between end-systole and end-diastole by almost 40 % as well as the error of the evaluation of the ejection fraction. Finally, to best exploit the fact that multiple reference images allow to reduce the registration displacement, we derived a symmetric and transitive registration that can be used both for frame-to-frame and frame-to-reference registration and further improves the accuracy of the registration.
机译:在本文中,我们提出了一种新颖的方法来研究4D图像序列中的心脏运动。传统方法依靠相对于通常对应于舒张末期(ED)图像的第一帧的整个序列配准,但我们使用重心子空间定义了更为通用的基础,该重心子空间由该序列的多个参考图像所覆盖。这些子空间被隐式定义为点的轨迹,这些点是k + 1个参考图像的加权Karcher均值。我们在心脏运动图像上建立这样的子空间,以获得不再由单个图像定义而是由系数(重心坐标)参数化的重心模板。我们首先显示,重心坐标(在心脏序列中运动的投影系数)定义了有意义的签名,可以对动力学进行逐组分析,并且可以有效地分离两个群体。然后,我们将重心模板用作心脏运动跟踪中常规化的先验,从而有效地将收缩末期和舒张末期之间的跟踪误差降低了近40%,并降低了射血分数的评估误差。最后,为了最好地利用多个参考图像可以减少配准位移的事实,我们导出了对称且可传递的配准,该配准可用于帧到帧和帧到参考的配准,并进一步提高了配准的准确性。登记。

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