使用 - 梯度流对电子断层扫描图像进行计算反演
Computational Inversion of Electron Tomography Images Using -Gradient Flows.
作者信息
Xu Guoliang, Li Ming, Gopinath Ajay, Bajaj Chandrajit
机构信息
State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing 100190, China.
Department of Computer Sciences and Institute of Computational Engineering & Sciences, University of Texas at Austin, Austin TX 78712.
出版信息
J Comput Math. 2011;29(5):501-525. doi: 10.4208/jcm.1103-m3261.
In this paper, we present a stable, reliable and robust method for reconstructing a three dimensional density function from a set of two dimensional electric tomographic images. By minimizing an energy functional consisting of a fidelity term and a regularization term, an -gradient flow is derived. The flow is integrated by a finite element method in the spatial direction and an explicit Euler scheme in temporal direction. The experimental results show that the proposed method is efficient and effective.
在本文中，我们提出了一种稳定、可靠且强大的方法，用于从一组二维电阻抗断层成像图像重建三维密度函数。通过最小化一个由保真项和正则项组成的能量泛函，推导出一个梯度流。该流在空间方向上通过有限元方法进行积分，在时间方向上通过显式欧拉格式进行积分。实验结果表明，所提出的方法是高效且有效的。
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