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Literature DB >> 17224280

Efficient automatic noise reduction of electron tomographic reconstructions based on iterative median filtering.

Peter van der Heide¹, Xiao-Ping Xu, Brad J Marsh, Dorit Hanein, Niels Volkmann.

Abstract

A simple, fast and efficient noise-reduction protocol for three-dimensional electron tomographic reconstructions of biological material is presented. The approach is based on iterative application of median filtering and shows promise for automatic noise reduction as a pre-processor for automated data analysis tools which aim at segmentation, feature extraction and pattern recognition. The application of this algorithm produces encouraging results for a wide variety of experimental and synthetic electron tomographic reconstructions.

Entities: Disease

Mesh：

Substances：
Multiprotein Complexes

Year: 2006 PMID： 17224280 DOI： 10.1016/j.jsb.2006.10.030

Source DB: PubMed Journal: J Struct Biol ISSN： 1047-8477 Impact factor: 2.867

Keyword Cloud
Cited

22 in total

9. Marker-free method for accurate alignment between correlated light, cryo-light, and electron cryo-microscopy data using sample support features.

Authors: Karen L Anderson; Christopher Page; Mark F Swift; Dorit Hanein; Niels Volkmann
Journal: J Struct Biol Date: 2017-11-04 Impact factor: 2.867

10. TOMOBFLOW: feature-preserving noise filtering for electron tomography.

Authors: Jose-Jesus Fernandez
Journal: BMC Bioinformatics Date: 2009-06-12 Impact factor: 3.169

Efficient automatic noise reduction of electron tomographic reconstructions based on iterative median filtering.

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9. Marker-free method for accurate alignment between correlated light, cryo-light, and electron cryo-microscopy data using sample support features.

10. TOMOBFLOW: feature-preserving noise filtering for electron tomography.