Automatic segmentation and measurement methods of living stomata of plants based on the CV model.
Identifieur interne : 000B14 ( Main/Exploration ); précédent : 000B13; suivant : 000B15Automatic segmentation and measurement methods of living stomata of plants based on the CV model.
Auteurs : Kexin Li [République populaire de Chine] ; Jianping Huang [République populaire de Chine] ; Wenlong Song [République populaire de Chine] ; Jingtao Wang [République populaire de Chine] ; Shuai Lv [République populaire de Chine] ; Xiuwei Wang [République populaire de Chine]Source :
- Plant methods [ 1746-4811 ] ; 2019.
Abstract
Background
The stomata of plants mainly regulate gas exchange and water dispersion between the interior and external environments of plants and play a major role in the plants' health. The existing methods of stomata segmentation and measurement are mostly for specialized plants. The purpose of this research is to develop a generic method for the fully automated segmentation and measurement of the living stomata of different plants. The proposed method utilizes level set theory and image processing technology and can outperform the existing stomata segmentation and measurement methods based on threshold and skeleton in terms of its versatility.
Results
The single stomata images of different plants were the input of the method and a level set based on the Chan-Vese model was used for stomatal segmentation. This allowed the morphological features of the stomata to be measured. Contrary to existing methods, the proposed segmentation method does not need any prior information about the stomata and is independent of the plant types. The segmentation results of 692 living stomata of black poplars show that the average measurement accuracies of the major and minor axes, area, eccentricity and opening degree are 95.68%, 95.53%, 93.04%, 99.46% and 94.32%, respectively. A segmentation test on dayflower (
Conclusions
The proposed automated segmentation and measurement method for living stomata is superior to the existing methods based on the threshold and skeletonization in terms of versatility. The method does not need any prior information about the stomata. It is an unconstrained segmentation method, which can accurately segment and measure the stomata for different types of plants (woody or herbs). The method can automatically discriminate whether the pore region is independent or not and perform pore region extraction. In addition, the segmentation accuracy of the method is positively correlated with the stomata's opening degree.
DOI: 10.1186/s13007-019-0453-5
PubMed: 31303890
PubMed Central: PMC6607599
Affiliations:
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China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin</wicri:regionArea><wicri:noRegion>Harbin</wicri:noRegion></affiliation></author><author><name sortKey="Song, Wenlong" sort="Song, Wenlong" uniqKey="Song W" first="Wenlong" last="Song">Wenlong Song</name><affiliation wicri:level="1"><nlm:affiliation>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin</wicri:regionArea><wicri:noRegion>Harbin</wicri:noRegion></affiliation></author><author><name sortKey="Wang, Jingtao" sort="Wang, Jingtao" uniqKey="Wang J" first="Jingtao" last="Wang">Jingtao Wang</name><affiliation wicri:level="1"><nlm:affiliation>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin</wicri:regionArea><wicri:noRegion>Harbin</wicri:noRegion></affiliation></author><author><name sortKey="Lv, Shuai" sort="Lv, Shuai" uniqKey="Lv S" first="Shuai" last="Lv">Shuai Lv</name><affiliation wicri:level="1"><nlm:affiliation>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin</wicri:regionArea><wicri:noRegion>Harbin</wicri:noRegion></affiliation></author><author><name sortKey="Wang, Xiuwei" sort="Wang, Xiuwei" uniqKey="Wang X" first="Xiuwei" last="Wang">Xiuwei Wang</name><affiliation wicri:level="1"><nlm:affiliation>2School of Forestry, NEFU, Harbin, 150040 China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>2School of Forestry, NEFU, Harbin</wicri:regionArea><wicri:noRegion>Harbin</wicri:noRegion></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2019">2019</date><idno type="RBID">pubmed:31303890</idno><idno type="pmid">31303890</idno><idno type="doi">10.1186/s13007-019-0453-5</idno><idno type="pmc">PMC6607599</idno><idno type="wicri:Area/Main/Corpus">000791</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000791</idno><idno type="wicri:Area/Main/Curation">000791</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">000791</idno><idno type="wicri:Area/Main/Exploration">000791</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Automatic segmentation and measurement methods of living stomata of plants based on the CV model.</title><author><name sortKey="Li, Kexin" sort="Li, Kexin" uniqKey="Li K" first="Kexin" last="Li">Kexin Li</name><affiliation wicri:level="1"><nlm:affiliation>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin</wicri:regionArea><wicri:noRegion>Harbin</wicri:noRegion></affiliation></author><author><name sortKey="Huang, Jianping" sort="Huang, Jianping" uniqKey="Huang J" first="Jianping" last="Huang">Jianping Huang</name><affiliation wicri:level="1"><nlm:affiliation>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin</wicri:regionArea><wicri:noRegion>Harbin</wicri:noRegion></affiliation></author><author><name sortKey="Song, Wenlong" sort="Song, Wenlong" uniqKey="Song W" first="Wenlong" last="Song">Wenlong Song</name><affiliation wicri:level="1"><nlm:affiliation>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin</wicri:regionArea><wicri:noRegion>Harbin</wicri:noRegion></affiliation></author><author><name sortKey="Wang, Jingtao" sort="Wang, Jingtao" uniqKey="Wang J" first="Jingtao" last="Wang">Jingtao Wang</name><affiliation wicri:level="1"><nlm:affiliation>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin</wicri:regionArea><wicri:noRegion>Harbin</wicri:noRegion></affiliation></author><author><name sortKey="Lv, Shuai" sort="Lv, Shuai" uniqKey="Lv S" first="Shuai" last="Lv">Shuai Lv</name><affiliation wicri:level="1"><nlm:affiliation>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin</wicri:regionArea><wicri:noRegion>Harbin</wicri:noRegion></affiliation></author><author><name sortKey="Wang, Xiuwei" sort="Wang, Xiuwei" uniqKey="Wang X" first="Xiuwei" last="Wang">Xiuwei Wang</name><affiliation wicri:level="1"><nlm:affiliation>2School of Forestry, NEFU, Harbin, 150040 China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>2School of Forestry, NEFU, Harbin</wicri:regionArea><wicri:noRegion>Harbin</wicri:noRegion></affiliation></author></analytic><series><title level="j">Plant methods</title><idno type="ISSN">1746-4811</idno><imprint><date when="2019" type="published">2019</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>Background</b></p><p>The stomata of plants mainly regulate gas exchange and water dispersion between the interior and external environments of plants and play a major role in the plants' health. The existing methods of stomata segmentation and measurement are mostly for specialized plants. The purpose of this research is to develop a generic method for the fully automated segmentation and measurement of the living stomata of different plants. The proposed method utilizes level set theory and image processing technology and can outperform the existing stomata segmentation and measurement methods based on threshold and skeleton in terms of its versatility.</p></div><div type="abstract" xml:lang="en"><p><b>Results</b></p><p>The single stomata images of different plants were the input of the method and a level set based on the Chan-Vese model was used for stomatal segmentation. This allowed the morphological features of the stomata to be measured. Contrary to existing methods, the proposed segmentation method does not need any prior information about the stomata and is independent of the plant types. The segmentation results of 692 living stomata of black poplars show that the average measurement accuracies of the major and minor axes, area, eccentricity and opening degree are 95.68%, 95.53%, 93.04%, 99.46% and 94.32%, respectively. A segmentation test on dayflower (</p></div><div type="abstract" xml:lang="en"><p><b>Conclusions</b></p><p>The proposed automated segmentation and measurement method for living stomata is superior to the existing methods based on the threshold and skeletonization in terms of versatility. The method does not need any prior information about the stomata. It is an unconstrained segmentation method, which can accurately segment and measure the stomata for different types of plants (woody or herbs). The method can automatically discriminate whether the pore region is independent or not and perform pore region extraction. In addition, the segmentation accuracy of the method is positively correlated with the stomata's opening degree.</p></div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">31303890</PMID><DateRevised><Year>2020</Year><Month>09</Month><Day>29</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">1746-4811</ISSN><JournalIssue CitedMedium="Print"><Volume>15</Volume><PubDate><Year>2019</Year></PubDate></JournalIssue><Title>Plant methods</Title><ISOAbbreviation>Plant Methods</ISOAbbreviation></Journal><ArticleTitle>Automatic segmentation and measurement methods of living stomata of plants based on the CV model.</ArticleTitle><Pagination><MedlinePgn>67</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1186/s13007-019-0453-5</ELocationID><Abstract><AbstractText Label="Background" NlmCategory="UNASSIGNED">The stomata of plants mainly regulate gas exchange and water dispersion between the interior and external environments of plants and play a major role in the plants' health. The existing methods of stomata segmentation and measurement are mostly for specialized plants. The purpose of this research is to develop a generic method for the fully automated segmentation and measurement of the living stomata of different plants. The proposed method utilizes level set theory and image processing technology and can outperform the existing stomata segmentation and measurement methods based on threshold and skeleton in terms of its versatility.</AbstractText><AbstractText Label="Results" NlmCategory="UNASSIGNED">The single stomata images of different plants were the input of the method and a level set based on the Chan-Vese model was used for stomatal segmentation. This allowed the morphological features of the stomata to be measured. Contrary to existing methods, the proposed segmentation method does not need any prior information about the stomata and is independent of the plant types. The segmentation results of 692 living stomata of black poplars show that the average measurement accuracies of the major and minor axes, area, eccentricity and opening degree are 95.68%, 95.53%, 93.04%, 99.46% and 94.32%, respectively. A segmentation test on dayflower (<i>Commelina benghalensis</i>) stomata data available in the literature was completed. The results show that the proposed method can effectively segment the stomata images (181 stomata) of dayflowers using bright-field microscopy. The fitted slope of the manually and automatically measured aperture is 0.993, and the R<sup>2</sup> value is 0.9828, which slightly outperforms the segmentation results that are given in the literature.</AbstractText><AbstractText Label="Conclusions" NlmCategory="UNASSIGNED">The proposed automated segmentation and measurement method for living stomata is superior to the existing methods based on the threshold and skeletonization in terms of versatility. The method does not need any prior information about the stomata. It is an unconstrained segmentation method, which can accurately segment and measure the stomata for different types of plants (woody or herbs). The method can automatically discriminate whether the pore region is independent or not and perform pore region extraction. In addition, the segmentation accuracy of the method is positively correlated with the stomata's opening degree.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Li</LastName><ForeName>Kexin</ForeName><Initials>K</Initials><AffiliationInfo><Affiliation>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin, China.</Affiliation><Identifier Source="ISNI">0000 0004 1789 9091</Identifier><Identifier Source="GRID">grid.412246.7</Identifier></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Huang</LastName><ForeName>Jianping</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin, China.</Affiliation><Identifier Source="ISNI">0000 0004 1789 9091</Identifier><Identifier Source="GRID">grid.412246.7</Identifier></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Song</LastName><ForeName>Wenlong</ForeName><Initials>W</Initials><AffiliationInfo><Affiliation>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin, China.</Affiliation><Identifier Source="ISNI">0000 0004 1789 9091</Identifier><Identifier Source="GRID">grid.412246.7</Identifier></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Jingtao</ForeName><Initials>J</Initials><AffiliationInfo><Affiliation>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin, China.</Affiliation><Identifier Source="ISNI">0000 0004 1789 9091</Identifier><Identifier Source="GRID">grid.412246.7</Identifier></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lv</LastName><ForeName>Shuai</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>1School of Mechanical and Electrical Engineering, Northeast Forestry University (NEFU), Harbin, China.</Affiliation><Identifier Source="ISNI">0000 0004 1789 9091</Identifier><Identifier Source="GRID">grid.412246.7</Identifier></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wang</LastName><ForeName>Xiuwei</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>2School of Forestry, NEFU, Harbin, 150040 China.</Affiliation><Identifier Source="ISNI">0000 0004 1789 9091</Identifier><Identifier Source="GRID">grid.412246.7</Identifier></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2019</Year><Month>07</Month><Day>03</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">Black poplar</Keyword><Keyword MajorTopicYN="N">CV model</Keyword><Keyword MajorTopicYN="N">Image processing</Keyword><Keyword MajorTopicYN="N">Living stomata</Keyword><Keyword MajorTopicYN="N">Pore measurement</Keyword><Keyword MajorTopicYN="N">Stomata segmentation</Keyword></KeywordList><CoiStatement>Competing interestsThe authors declare that they have no competing interests.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2019</Year><Month>02</Month><Day>02</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2019</Year><Month>06</Month><Day>28</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2019</Year><Month>7</Month><Day>16</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2019</Year><Month>7</Month><Day>16</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2019</Year><Month>7</Month><Day>16</Day><Hour>6</Hour><Minute>1</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">31303890</ArticleId><ArticleId IdType="doi">10.1186/s13007-019-0453-5</ArticleId><ArticleId IdType="pii">453</ArticleId><ArticleId IdType="pmc">PMC6607599</ArticleId></ArticleIdList><ReferenceList><Reference><Citation>Genes Dev. 2000 May 1;14(9):1119-31</Citation><ArticleIdList><ArticleId IdType="pubmed">10809670</ArticleId></ArticleIdList></Reference><Reference><Citation>Nature. 2003 Aug 21;424(6951):901-8</Citation><ArticleIdList><ArticleId IdType="pubmed">12931178</ArticleId></ArticleIdList></Reference><Reference><Citation>IEEE Trans Image Process. 2001;10(2):266-77</Citation><ArticleIdList><ArticleId IdType="pubmed">18249617</ArticleId></ArticleIdList></Reference><Reference><Citation>Evodevo. 2012 Jul 06;3(1):11</Citation><ArticleIdList><ArticleId IdType="pubmed">22691547</ArticleId></ArticleIdList></Reference><Reference><Citation>IEEE Trans Pattern Anal Mach Intell. 2017 Jun;39(6):1137-1149</Citation><ArticleIdList><ArticleId IdType="pubmed">27295650</ArticleId></ArticleIdList></Reference><Reference><Citation>Plant Methods. 2017 Nov 8;13:94</Citation><ArticleIdList><ArticleId IdType="pubmed">29151841</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed><affiliations><list><country><li>République populaire de Chine</li></country></list><tree><country name="République populaire de Chine"><noRegion><name sortKey="Li, Kexin" sort="Li, Kexin" uniqKey="Li K" first="Kexin" last="Li">Kexin Li</name></noRegion><name sortKey="Huang, Jianping" sort="Huang, Jianping" uniqKey="Huang J" first="Jianping" last="Huang">Jianping Huang</name><name sortKey="Lv, Shuai" sort="Lv, Shuai" uniqKey="Lv S" first="Shuai" last="Lv">Shuai Lv</name><name sortKey="Song, Wenlong" sort="Song, Wenlong" uniqKey="Song W" first="Wenlong" last="Song">Wenlong Song</name><name sortKey="Wang, Jingtao" sort="Wang, Jingtao" uniqKey="Wang J" first="Jingtao" last="Wang">Jingtao Wang</name><name sortKey="Wang, Xiuwei" sort="Wang, Xiuwei" uniqKey="Wang X" first="Xiuwei" last="Wang">Xiuwei Wang</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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