Unknown

Dataset Information

0

Electric-Potential Reconstructions of Single Particles Using L-Gradient Flows.


ABSTRACT: In this paper, we present a stable, reliable and robust method for reconstructing a three dimensional density function from a set of two dimensional electron microscopy images. By minimizing an energy functional consisting of a fidelity term and a regularization term, a 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.

SUBMITTER: Li M 

PROVIDER: S-EPMC3091820 | biostudies-literature | 2010 Oct

REPOSITORIES: biostudies-literature

altmetric image

Publications

Electric-Potential Reconstructions of Single Particles Using L-Gradient Flows.

Li Ming M   Xu Guoliang G   Sorzano Carlos O S CO   Melero Roberto R   Bajaj Chandrajit C  

Proceedings of the ... International Conference on Biomedical Engineering and Informatics. International Conference on Biomedical Engineering and Informatics 20101001


In this paper, we present a stable, reliable and robust method for reconstructing a three dimensional density function from a set of two dimensional electron microscopy images. By minimizing an energy functional consisting of a fidelity term and a regularization term, a 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  ...[more]

Similar Datasets

| S-EPMC3498508 | biostudies-literature
| S-EPMC2838734 | biostudies-literature
| S-EPMC6154969 | biostudies-literature
| S-EPMC7438090 | biostudies-literature
| S-EPMC4958462 | biostudies-literature
| S-EPMC4968475 | biostudies-other
| S-EPMC7568292 | biostudies-literature
| S-EPMC7578653 | biostudies-literature
| S-EPMC2768593 | biostudies-literature
| S-EPMC9826812 | biostudies-literature