A VECTOR MOMENTA FORMULATION OF DIFFEOMORPHISMS FOR IMPROVED GEODESIC REGRESSION AND ATLAS CONSTRUCTION.
A VECTOR MOMENTA FORMULATION OF DIFFEOMORPHISMS FOR IMPROVED GEODESIC REGRESSION AND ATLAS CONSTRUCTION.
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DOI：
10.1109/isbi.2013.6556700
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发表时间：
2013-04
期刊：
影响因子：
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通讯作者：
Fletcher PT
中科院分区：
文献类型：
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作者：
Singh N;Hinkle J;Joshi S;Fletcher PT
本文提出了一种微分同胚图像回归和图谱估计的新方法，可提高收敛性和数值稳定性。我们使用微分同胚初始条件的矢量动量表示，而不是通常使用的标准标量动量。相应的变分问题导致测地线回归和图集估计问题中模板估计的封闭形式更新。虽然我们表明理论最优解等效于标量动量情况，但优化问题的简化导致实践中的估计更加稳定和有效。我们使用合成生成的形状和 3D MRI 脑扫描证明了我们的图集估计和测地线回归方法的有效性。
This paper presents a novel approach for diffeomorphic image regression and atlas estimation that results in improved convergence and numerical stability. We use a vector momenta representation of a diffeomorphism's initial conditions instead of the standard scalar momentum that is typically used. The corresponding variational problem results in a closed-form update for template estimation in both the geodesic regression and atlas estimation problems. While we show that the theoretical optimal solution is equivalent to the scalar momenta case, the simplification of the optimization problem leads to more stable and efficient estimation in practice. We demonstrate the effectiveness of our method for atlas estimation and geodesic regression using synthetically generated shapes and 3D MRI brain scans.