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Automated stitching of microtubule centerlines across serial electron tomograms
Tracing microtubule centerlines in serial section electron tomography requires microtubules to be stitched across sections, that is lines from different sections need to be aligned, endpoints need to be matched at section boundaries to establish a correspondence between neighboring sections, and cor...
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Published in: | PloS one 2014-12, Vol.9 (12), p.e113222-e113222 |
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description | Tracing microtubule centerlines in serial section electron tomography requires microtubules to be stitched across sections, that is lines from different sections need to be aligned, endpoints need to be matched at section boundaries to establish a correspondence between neighboring sections, and corresponding lines need to be connected across multiple sections. We present computational methods for these tasks: 1) An initial alignment is computed using a distance compatibility graph. 2) A fine alignment is then computed with a probabilistic variant of the iterative closest points algorithm, which we extended to handle the orientation of lines by introducing a periodic random variable to the probabilistic formulation. 3) Endpoint correspondence is established by formulating a matching problem in terms of a Markov random field and computing the best matching with belief propagation. Belief propagation is not generally guaranteed to converge to a minimum. We show how convergence can be achieved, nonetheless, with minimal manual input. In addition to stitching microtubule centerlines, the correspondence is also applied to transform and merge the electron tomograms. We applied the proposed methods to samples from the mitotic spindle in C. elegans, the meiotic spindle in X. laevis, and sub-pellicular microtubule arrays in T. brucei. The methods were able to stitch microtubules across section boundaries in good agreement with experts' opinions for the spindle samples. Results, however, were not satisfactory for the microtubule arrays. For certain experiments, such as an analysis of the spindle, the proposed methods can replace manual expert tracing and thus enable the analysis of microtubules over long distances with reasonable manual effort. |
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We present computational methods for these tasks: 1) An initial alignment is computed using a distance compatibility graph. 2) A fine alignment is then computed with a probabilistic variant of the iterative closest points algorithm, which we extended to handle the orientation of lines by introducing a periodic random variable to the probabilistic formulation. 3) Endpoint correspondence is established by formulating a matching problem in terms of a Markov random field and computing the best matching with belief propagation. Belief propagation is not generally guaranteed to converge to a minimum. We show how convergence can be achieved, nonetheless, with minimal manual input. In addition to stitching microtubule centerlines, the correspondence is also applied to transform and merge the electron tomograms. We applied the proposed methods to samples from the mitotic spindle in C. elegans, the meiotic spindle in X. laevis, and sub-pellicular microtubule arrays in T. brucei. The methods were able to stitch microtubules across section boundaries in good agreement with experts' opinions for the spindle samples. Results, however, were not satisfactory for the microtubule arrays. For certain experiments, such as an analysis of the spindle, the proposed methods can replace manual expert tracing and thus enable the analysis of microtubules over long distances with reasonable manual effort.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0113222</identifier><identifier>PMID: 25438148</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Alignment ; Animals ; Automation ; Biology and Life Sciences ; Boundaries ; Caenorhabditis elegans - cytology ; Cell cycle ; Cell division ; Computation ; Computer applications ; Convergence ; Deformation ; Elasticity ; Electron Microscope Tomography ; Electrons ; Image Processing, Computer-Assisted - methods ; Iterative methods ; Laboratories ; Markov processes ; Matching ; Meiosis ; Methods ; Microscopy ; Microtubules ; Microtubules - metabolism ; Molecular biology ; Oocytes - cytology ; Physical Sciences ; Propagation ; Random variables ; Research and Analysis Methods ; Software ; Spindle Apparatus - metabolism ; Stitching ; Tomography ; Trypanosoma brucei brucei - cytology ; Xenopus laevis</subject><ispartof>PloS one, 2014-12, Vol.9 (12), p.e113222-e113222</ispartof><rights>COPYRIGHT 2014 Public Library of Science</rights><rights>2014 Weber et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. 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For certain experiments, such as an analysis of the spindle, the proposed methods can replace manual expert tracing and thus enable the analysis of microtubules over long distances with reasonable manual effort.</description><subject>Algorithms</subject><subject>Alignment</subject><subject>Animals</subject><subject>Automation</subject><subject>Biology and Life Sciences</subject><subject>Boundaries</subject><subject>Caenorhabditis elegans - cytology</subject><subject>Cell cycle</subject><subject>Cell division</subject><subject>Computation</subject><subject>Computer applications</subject><subject>Convergence</subject><subject>Deformation</subject><subject>Elasticity</subject><subject>Electron Microscope Tomography</subject><subject>Electrons</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Iterative methods</subject><subject>Laboratories</subject><subject>Markov processes</subject><subject>Matching</subject><subject>Meiosis</subject><subject>Methods</subject><subject>Microscopy</subject><subject>Microtubules</subject><subject>Microtubules - 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We present computational methods for these tasks: 1) An initial alignment is computed using a distance compatibility graph. 2) A fine alignment is then computed with a probabilistic variant of the iterative closest points algorithm, which we extended to handle the orientation of lines by introducing a periodic random variable to the probabilistic formulation. 3) Endpoint correspondence is established by formulating a matching problem in terms of a Markov random field and computing the best matching with belief propagation. Belief propagation is not generally guaranteed to converge to a minimum. We show how convergence can be achieved, nonetheless, with minimal manual input. In addition to stitching microtubule centerlines, the correspondence is also applied to transform and merge the electron tomograms. We applied the proposed methods to samples from the mitotic spindle in C. elegans, the meiotic spindle in X. laevis, and sub-pellicular microtubule arrays in T. brucei. 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subjects | Algorithms Alignment Animals Automation Biology and Life Sciences Boundaries Caenorhabditis elegans - cytology Cell cycle Cell division Computation Computer applications Convergence Deformation Elasticity Electron Microscope Tomography Electrons Image Processing, Computer-Assisted - methods Iterative methods Laboratories Markov processes Matching Meiosis Methods Microscopy Microtubules Microtubules - metabolism Molecular biology Oocytes - cytology Physical Sciences Propagation Random variables Research and Analysis Methods Software Spindle Apparatus - metabolism Stitching Tomography Trypanosoma brucei brucei - cytology Xenopus laevis |
title | Automated stitching of microtubule centerlines across serial electron tomograms |
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