An Improved Quantitative Analysis Method for Plant Cortical Microtubules

The arrangement of plant cortical microtubules can reflect the physiological state of cells. However, little attention has been paid to the image quantitative analysis of plant cortical microtubules so far. In this paper, Bidimensional Empirical Mode Decomposition (BEMD) algorithm was applied in the...

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Main Authors: Yi Lu, Chenyang Huang, Jia Wang, Peng Shang
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:The Scientific World Journal
Online Access:http://dx.doi.org/10.1155/2014/637183
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author Yi Lu
Chenyang Huang
Jia Wang
Peng Shang
author_facet Yi Lu
Chenyang Huang
Jia Wang
Peng Shang
author_sort Yi Lu
collection DOAJ
description The arrangement of plant cortical microtubules can reflect the physiological state of cells. However, little attention has been paid to the image quantitative analysis of plant cortical microtubules so far. In this paper, Bidimensional Empirical Mode Decomposition (BEMD) algorithm was applied in the image preprocessing of the original microtubule image. And then Intrinsic Mode Function 1 (IMF1) image obtained by decomposition was selected to do the texture analysis based on Grey-Level Cooccurrence Matrix (GLCM) algorithm. Meanwhile, in order to further verify its reliability, the proposed texture analysis method was utilized to distinguish different images of Arabidopsis microtubules. The results showed that the effect of BEMD algorithm on edge preserving accompanied with noise reduction was positive, and the geometrical characteristic of the texture was obvious. Four texture parameters extracted by GLCM perfectly reflected the different arrangements between the two images of cortical microtubules. In summary, the results indicate that this method is feasible and effective for the image quantitative analysis of plant cortical microtubules. It not only provides a new quantitative approach for the comprehensive study of the role played by microtubules in cell life activities but also supplies references for other similar studies.
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publishDate 2014-01-01
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spelling doaj-art-b99a190d32534cb59b4fc8a9c7ca55ae2025-02-03T01:12:20ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/637183637183An Improved Quantitative Analysis Method for Plant Cortical MicrotubulesYi Lu0Chenyang Huang1Jia Wang2Peng Shang3School of Life Sciences, Northwestern Polytechnical University, 127 Youyi xilu, Xi’an, Shaanxi 710072, ChinaSchool of Science, Northwestern Polytechnical University, 127 Youyi xilu, Xi’an, Shaanxi 710072, ChinaSchool of Life Sciences, Northwestern Polytechnical University, 127 Youyi xilu, Xi’an, Shaanxi 710072, ChinaSchool of Life Sciences, Northwestern Polytechnical University, 127 Youyi xilu, Xi’an, Shaanxi 710072, ChinaThe arrangement of plant cortical microtubules can reflect the physiological state of cells. However, little attention has been paid to the image quantitative analysis of plant cortical microtubules so far. In this paper, Bidimensional Empirical Mode Decomposition (BEMD) algorithm was applied in the image preprocessing of the original microtubule image. And then Intrinsic Mode Function 1 (IMF1) image obtained by decomposition was selected to do the texture analysis based on Grey-Level Cooccurrence Matrix (GLCM) algorithm. Meanwhile, in order to further verify its reliability, the proposed texture analysis method was utilized to distinguish different images of Arabidopsis microtubules. The results showed that the effect of BEMD algorithm on edge preserving accompanied with noise reduction was positive, and the geometrical characteristic of the texture was obvious. Four texture parameters extracted by GLCM perfectly reflected the different arrangements between the two images of cortical microtubules. In summary, the results indicate that this method is feasible and effective for the image quantitative analysis of plant cortical microtubules. It not only provides a new quantitative approach for the comprehensive study of the role played by microtubules in cell life activities but also supplies references for other similar studies.http://dx.doi.org/10.1155/2014/637183
spellingShingle Yi Lu
Chenyang Huang
Jia Wang
Peng Shang
An Improved Quantitative Analysis Method for Plant Cortical Microtubules
The Scientific World Journal
title An Improved Quantitative Analysis Method for Plant Cortical Microtubules
title_full An Improved Quantitative Analysis Method for Plant Cortical Microtubules
title_fullStr An Improved Quantitative Analysis Method for Plant Cortical Microtubules
title_full_unstemmed An Improved Quantitative Analysis Method for Plant Cortical Microtubules
title_short An Improved Quantitative Analysis Method for Plant Cortical Microtubules
title_sort improved quantitative analysis method for plant cortical microtubules
url http://dx.doi.org/10.1155/2014/637183
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