TY - JOUR
T1 - Inversion of Electron Tomography Images Using $L^2$-Gradient Flows — Computational Methods
AU - Guoliang Xu, Ming Li, Ajay Gopinath, & Chandrajit L. Bajaj
JO - Journal of Computational Mathematics
VL - 5
SP - 501
EP - 525
PY - 2011
DA - 2011/10
SN - 29
DO - http://doi.org/10.4208/jcm.1106-m3302
UR - https://global-sci.org/intro/article_detail/jcm/8491.html
KW - Computational Inversion, Reconstruction, Electric Tomography.
AB - <p style="text-align: justify;">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 $L^2$-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.</p>