Name
Abstract | ||
|---|---|---|
The selection of single particles from an electron microscopic (EM) micrograph is an essential part of the reconstruction process of biological macromolecules. Despite its importance, this process requires a lot of user intervention by either purely manual or semi-automatic processing (with the aid of graphical interfaces). Since reconstructing a 3D model of these macromolecules at nano-scale resolution requires thousands of particles, the particle selection phase is bound to become a serious bottleneck in the reconstruction process. In this article we propose a semi-automatic procedure for selecting particles from a micrograph that aims to reduce the false positive rate. We achieve this by first using a fuzzy-sets-based segmentation method, that requires very little user intervention, to detect the background, and then calculating a cross-correlation measure only on points with low "affinity" to the micrograph's background. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ISBI.2006.1625095 | 2006 3RD IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: MACRO TO NANO, VOLS 1-3 |
Keywords | Field | DocType |
fuzzy sets,graphical interface,fuzzy set,image reconstruction,crystallization,circuits,electron microscopy,image segmentation,biological processes,dna,cross correlation,molecular biophysics,false positive rate,proteins,electron microscope,fuzzy set theory | Iterative reconstruction,False positive rate,Computer vision,Bottleneck,Pattern recognition,Segmentation,Computer science,Image segmentation,Artificial intelligence,Micrograph,Particle,Electron | Conference |
ISSN | Citations | PageRank |
1945-7928 | 2 | 0.66 |
References | Authors | |
2 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bruno M. Carvalho | 1 | 182 | 19.31 |
| Lucas M. Oliveira | 2 | 14 | 3.62 |
| Edgar Garduño | 3 | 44 | 8.03 |