High-efficiency procedure to characterize, segment, and quantify complex multicellularity in raw micrographs in plants.
Identifieur interne : 000352 ( Main/Exploration ); précédent : 000351; suivant : 000353High-efficiency procedure to characterize, segment, and quantify complex multicellularity in raw micrographs in plants.
Auteurs : Xi Zhang [République populaire de Chine] ; Zijian Hu [République populaire de Chine] ; Yayu Guo [République populaire de Chine] ; Xiaoyi Shan [République populaire de Chine] ; Xiaojuan Li [République populaire de Chine] ; Jinxing Lin [République populaire de Chine]Source :
- Plant methods [ 1746-4811 ] ; 2020.
Abstract
Background
The increasing number of novel approaches for large-scale, multi-dimensional imaging of cells has created an unprecedented opportunity to analyze plant morphogenesis. However, complex image processing, including identifying specific cells and quantitating parameters, and high running cost of some image analysis softwares remains challenging. Therefore, it is essential to develop an efficient method for identifying plant complex multicellularity in raw micrographs in plants.
Results
Here, we developed a high-efficiency procedure to characterize, segment, and quantify plant multicellularity in various raw images using the open-source software packages ImageJ and SR-Tesseler. This procedure allows for the rapid, accurate, automatic quantification of cell patterns and organization at different scales, from large tissues down to the cellular level. We validated our method using different images captured from
Conclusions
This procedure can be used to determine the character and organization of multicellular plant tissues at high efficiency, including precise parameter identification and polygon-based segmentation of plant cells.
DOI: 10.1186/s13007-020-00642-0
PubMed: 32742298
PubMed Central: PMC7390866
Affiliations:
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first="Zijian" last="Hu">Zijian Hu</name><affiliation wicri:level="3"><nlm:affiliation>College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, 10083 China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation></author><author><name sortKey="Guo, Yayu" sort="Guo, Yayu" uniqKey="Guo Y" first="Yayu" last="Guo">Yayu Guo</name><affiliation wicri:level="3"><nlm:affiliation>College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, 10083 China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing</wicri:regionArea><placeName><settlement 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type="abstract" xml:lang="en"><p><b>Background</b></p><p>The increasing number of novel approaches for large-scale, multi-dimensional imaging of cells has created an unprecedented opportunity to analyze plant morphogenesis. However, complex image processing, including identifying specific cells and quantitating parameters, and high running cost of some image analysis softwares remains challenging. Therefore, it is essential to develop an efficient method for identifying plant complex multicellularity in raw micrographs in plants.</p></div><div type="abstract" xml:lang="en"><p><b>Results</b></p><p>Here, we developed a high-efficiency procedure to characterize, segment, and quantify plant multicellularity in various raw images using the open-source software packages ImageJ and SR-Tesseler. This procedure allows for the rapid, accurate, automatic quantification of cell patterns and organization at different scales, from large tissues down to the cellular level. We validated our method using different images captured from </p></div><div type="abstract" xml:lang="en"><p><b>Conclusions</b></p><p>This procedure can be used to determine the character and organization of multicellular plant tissues at high efficiency, including precise parameter identification and polygon-based segmentation of plant cells.</p></div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">32742298</PMID><DateRevised><Year>2020</Year><Month>09</Month><Day>28</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">1746-4811</ISSN><JournalIssue CitedMedium="Print"><Volume>16</Volume><PubDate><Year>2020</Year></PubDate></JournalIssue><Title>Plant methods</Title><ISOAbbreviation>Plant Methods</ISOAbbreviation></Journal><ArticleTitle>High-efficiency procedure to characterize, segment, and quantify complex multicellularity in raw micrographs in plants.</ArticleTitle><Pagination><MedlinePgn>100</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/s13007-020-00642-0</ELocationID><Abstract><AbstractText Label="Background" NlmCategory="UNASSIGNED">The increasing number of novel approaches for large-scale, multi-dimensional imaging of cells has created an unprecedented opportunity to analyze plant morphogenesis. However, complex image processing, including identifying specific cells and quantitating parameters, and high running cost of some image analysis softwares remains challenging. Therefore, it is essential to develop an efficient method for identifying plant complex multicellularity in raw micrographs in plants.</AbstractText><AbstractText Label="Results" NlmCategory="UNASSIGNED">Here, we developed a high-efficiency procedure to characterize, segment, and quantify plant multicellularity in various raw images using the open-source software packages ImageJ and SR-Tesseler. This procedure allows for the rapid, accurate, automatic quantification of cell patterns and organization at different scales, from large tissues down to the cellular level. We validated our method using different images captured from <i>Arabidopsis thaliana</i> roots and seeds and <i>Populus tremula</i> stems, including fluorescently labeled images, Micro-CT scans, and dyed sections. Finally, we determined the area, centroid coordinate, perimeter, and Feret's diameter of the cells and harvested the cell distribution patterns from Voronoï diagrams by setting the threshold at localization density, mean distance, or area.</AbstractText><AbstractText Label="Conclusions" NlmCategory="UNASSIGNED">This procedure can be used to determine the character and organization of multicellular plant tissues at high efficiency, including precise parameter identification and polygon-based segmentation of plant cells.</AbstractText><CopyrightInformation>© The Author(s) 2020.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y" EqualContrib="Y"><LastName>Zhang</LastName><ForeName>Xi</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, 10083 China.</Affiliation><Identifier Source="GRID">grid.66741.32</Identifier><Identifier Source="ISNI">0000 0001 1456 856X</Identifier></AffiliationInfo></Author><Author ValidYN="Y" EqualContrib="Y"><LastName>Hu</LastName><ForeName>Zijian</ForeName><Initials>Z</Initials><AffiliationInfo><Affiliation>College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, 10083 China.</Affiliation><Identifier Source="GRID">grid.66741.32</Identifier><Identifier Source="ISNI">0000 0001 1456 856X</Identifier></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Guo</LastName><ForeName>Yayu</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, 10083 China.</Affiliation><Identifier Source="GRID">grid.66741.32</Identifier><Identifier Source="ISNI">0000 0001 1456 856X</Identifier></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Shan</LastName><ForeName>Xiaoyi</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, 10083 China.</Affiliation><Identifier Source="GRID">grid.66741.32</Identifier><Identifier Source="ISNI">0000 0001 1456 856X</Identifier></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Li</LastName><ForeName>Xiaojuan</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, 10083 China.</Affiliation><Identifier Source="GRID">grid.66741.32</Identifier><Identifier Source="ISNI">0000 0001 1456 856X</Identifier></AffiliationInfo><AffiliationInfo><Affiliation>College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, 10083 China.</Affiliation><Identifier Source="GRID">grid.66741.32</Identifier><Identifier Source="ISNI">0000 0001 1456 856X</Identifier></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lin</LastName><ForeName>Jinxing</ForeName><Initials>J</Initials><Identifier Source="ORCID">0000-0001-9338-1356</Identifier><AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University, Beijing, 10083 China.</Affiliation><Identifier Source="GRID">grid.66741.32</Identifier><Identifier Source="ISNI">0000 0001 1456 856X</Identifier></AffiliationInfo><AffiliationInfo><Affiliation>College of Biological Sciences and Biotechnology, Beijing Forestry University, Beijing, 10083 China.</Affiliation><Identifier Source="GRID">grid.66741.32</Identifier><Identifier Source="ISNI">0000 0001 1456 856X</Identifier></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>07</Month><Day>28</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Plant Methods</MedlineTA><NlmUniqueID>101245798</NlmUniqueID><ISSNLinking>1746-4811</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Image processing</Keyword><Keyword MajorTopicYN="N">Large-scale imaging</Keyword><Keyword MajorTopicYN="N">Morphogenesis</Keyword><Keyword MajorTopicYN="N">Parameters</Keyword><Keyword MajorTopicYN="N">Plant multicellularity</Keyword></KeywordList><CoiStatement>Competing interestsThe authors declare that they have no competing interests.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>05</Month><Day>28</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>07</Month><Day>20</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>8</Month><Day>4</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate 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