Literature DB >> 20719286

Automated identification of microtubules in cellular electron tomography.

Daniyar Nurgaliev1, Timur Gatanov, Daniel J Needleman.   

Abstract

We describe a method for automatically finding the location and conformations of microtubules in tomograms of high-pressure frozen, freeze substituted cells. Our approach uses two steps: a preprocessing step that finds locations in the tomograms that are likely to lie inside microtubules and a tracking step that uses the preprocessed data to identify the trajectories of individual microtubules. We test this method on a reconstruction of a Caenorhabditis elegans mitotic spindle and we compare our results with those obtained by a human expert who manually segmented the same data. At present, the method could be used to assist the analysis of large-scale tomography reconstructions. With further improvements, it may be possible to reliably segment cellular tomograms without human intervention. 2010 Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20719286     DOI: 10.1016/S0091-679X(10)97025-8

Source DB:  PubMed          Journal:  Methods Cell Biol        ISSN: 0091-679X            Impact factor:   1.441


  3 in total

1.  EXTRACTION AND ANALYSIS OF ACTIN NETWORKS BASED ON OPEN ACTIVE CONTOUR MODELS.

Authors:  Ting Xu; Hongsheng Li; Tian Shen; Nikola Ojkic; Dimitrios Vavylonis; Xiaolei Huang
Journal:  Proc IEEE Int Symp Biomed Imaging       Date:  2011-03-30

2.  3D actin network centerline extraction with multiple active contours.

Authors:  Ting Xu; Dimitrios Vavylonis; Xiaolei Huang
Journal:  Med Image Anal       Date:  2013-11-16       Impact factor: 8.545

3.  Extracting microtubule networks from superresolution single-molecule localization microscopy data.

Authors:  Zhen Zhang; Yukako Nishimura; Pakorn Kanchanawong
Journal:  Mol Biol Cell       Date:  2016-11-16       Impact factor: 4.138

  3 in total

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