Mammographic mass segmentation using fuzzy contours.
Identifieur interne : 000339 ( Main/Exploration ); précédent : 000338; suivant : 000340Mammographic mass segmentation using fuzzy contours.
Auteurs : Marwa Hmida [France] ; Kamel Hamrouni [Tunisie] ; Basel Solaiman [France] ; Sana Boussetta [Tunisie]Source :
- Computer methods and programs in biomedicine [ 1872-7565 ] ; 2018.
Descripteurs français
- KwdFr :
- Bases de données factuelles (statistiques et données numériques), Diagnostic assisté par ordinateur (méthodes), Diagnostic assisté par ordinateur (statistiques et données numériques), Femelle (MeSH), Humains (MeSH), Interprétation d'images radiographiques assistée par ordinateur (méthodes), Interprétation d'images radiographiques assistée par ordinateur (statistiques et données numériques), Logique floue (MeSH), Mammographie (méthodes), Mammographie (statistiques et données numériques), Tumeurs du sein (imagerie diagnostique).
- MESH :
- imagerie diagnostique : Tumeurs du sein.
- méthodes : Diagnostic assisté par ordinateur, Interprétation d'images radiographiques assistée par ordinateur, Mammographie.
- statistiques et données numériques : Bases de données factuelles, Diagnostic assisté par ordinateur, Interprétation d'images radiographiques assistée par ordinateur, Mammographie.
- Femelle, Humains, Logique floue.
English descriptors
- KwdEn :
- Breast Neoplasms (diagnostic imaging), Databases, Factual (statistics & numerical data), Diagnosis, Computer-Assisted (methods), Diagnosis, Computer-Assisted (statistics & numerical data), Female (MeSH), Fuzzy Logic (MeSH), Humans (MeSH), Mammography (methods), Mammography (statistics & numerical data), Radiographic Image Interpretation, Computer-Assisted (methods), Radiographic Image Interpretation, Computer-Assisted (statistics & numerical data).
- MESH :
- diagnostic imaging : Breast Neoplasms.
- methods : Diagnosis, Computer-Assisted, Mammography, Radiographic Image Interpretation, Computer-Assisted.
- statistics & numerical data : Databases, Factual, Diagnosis, Computer-Assisted, Mammography, Radiographic Image Interpretation, Computer-Assisted.
- Female, Fuzzy Logic, Humans.
Abstract
BACKGROUND AND OBJECTIVE
Accurate mass segmentation in mammographic images is a critical requirement for computer-aided diagnosis systems since it allows accurate feature extraction and thus improves classification precision.
METHODS
In this paper, a novel automatic breast mass segmentation approach is presented. This approach consists of mainly three stages: contour initialization applied to a given region of interest; construction of fuzzy contours and estimation of fuzzy membership maps of different classes in the considered image; integration of these maps in the Chan-Vese model to get a fuzzy-energy based model that is used for final delineation of mass.
RESULTS
The proposed approach is evaluated using mass regions of interest extracted from the mini-MIAS database. The experimental results show that the proposed method achieves an average true positive rate of 91.12% with a precision of 88.08%.
CONCLUSIONS
The achieved results show high accuracy in breast mass segmentation when compared to manually annotated ground truth and to other methods from the literature.
DOI: 10.1016/j.cmpb.2018.07.005
PubMed: 30195421
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Mammographic mass segmentation using fuzzy contours.</title><author><name sortKey="Hmida, Marwa" sort="Hmida, Marwa" uniqKey="Hmida M" first="Marwa" last="Hmida">Marwa Hmida</name><affiliation wicri:level="4"><nlm:affiliation>Université de Tunis El Manar, Ecole Nationale d'Ingnieurs de Tunis, LR-Signal Image et Technologies de l'Information, Tunis 1002, Tunisie; IMT Atlantique, ITI Laboratory, Brest 29238, France. Electronic address: marwa.hmida@telecom-bretagne.eu.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Université de Tunis El Manar, Ecole Nationale d'Ingnieurs de Tunis, LR-Signal Image et Technologies de l'Information, Tunis 1002, Tunisie; IMT Atlantique, ITI Laboratory, Brest 29238</wicri:regionArea><placeName><region type="region" nuts="2">Région Bretagne</region></placeName><orgName type="university">Université de Tunis - El Manar</orgName></affiliation></author><author><name sortKey="Hamrouni, Kamel" sort="Hamrouni, Kamel" uniqKey="Hamrouni K" first="Kamel" last="Hamrouni">Kamel Hamrouni</name><affiliation wicri:level="4"><nlm:affiliation>Université de Tunis El Manar, Ecole Nationale d'Ingnieurs de Tunis, LR-Signal Image et Technologies de l'Information, Tunis 1002, Tunisie. Electronic address: kamel.hamrouni@gmail.com.</nlm:affiliation><country xml:lang="fr">Tunisie</country><wicri:regionArea>Université de Tunis El Manar, Ecole Nationale d'Ingnieurs de Tunis, LR-Signal Image et Technologies de l'Information, Tunis 1002</wicri:regionArea><placeName><settlement type="city">Tunis</settlement><region nuts="2">Gouvernorat de Tunis</region></placeName><orgName type="university">Université de Tunis - El Manar</orgName><placeName><settlement type="city">Tunis</settlement><region type="region" nuts="2">Gouvernorat de Tunis</region></placeName></affiliation></author><author><name sortKey="Solaiman, Basel" sort="Solaiman, Basel" uniqKey="Solaiman B" first="Basel" last="Solaiman">Basel Solaiman</name><affiliation wicri:level="3"><nlm:affiliation>IMT Atlantique, ITI Laboratory, Brest 29238, France. Electronic address: basel.solaiman@telecom-bretagne.eu.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>IMT Atlantique, ITI Laboratory, Brest 29238</wicri:regionArea><placeName><region type="region" nuts="2">Région Bretagne</region></placeName></affiliation></author><author><name sortKey="Boussetta, Sana" sort="Boussetta, Sana" uniqKey="Boussetta S" first="Sana" last="Boussetta">Sana Boussetta</name><affiliation wicri:level="1"><nlm:affiliation>Regional hospital of Ben Arous, Tunisia. Electronic address: sana_boussetta@yahoo.fr.</nlm:affiliation><country xml:lang="fr">Tunisie</country><wicri:regionArea>Regional hospital of Ben Arous</wicri:regionArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2018">2018</date><idno type="RBID">pubmed:30195421</idno><idno type="pmid">30195421</idno><idno type="doi">10.1016/j.cmpb.2018.07.005</idno><idno type="wicri:Area/Main/Corpus">000324</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000324</idno><idno type="wicri:Area/Main/Curation">000324</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">000324</idno><idno type="wicri:Area/Main/Exploration">000324</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Mammographic mass segmentation using fuzzy contours.</title><author><name sortKey="Hmida, Marwa" sort="Hmida, Marwa" uniqKey="Hmida M" first="Marwa" last="Hmida">Marwa Hmida</name><affiliation wicri:level="4"><nlm:affiliation>Université de Tunis El Manar, Ecole Nationale d'Ingnieurs de Tunis, LR-Signal Image et Technologies de l'Information, Tunis 1002, Tunisie; IMT Atlantique, ITI Laboratory, Brest 29238, France. Electronic address: marwa.hmida@telecom-bretagne.eu.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Université de Tunis El Manar, Ecole Nationale d'Ingnieurs de Tunis, LR-Signal Image et Technologies de l'Information, Tunis 1002, Tunisie; IMT Atlantique, ITI Laboratory, Brest 29238</wicri:regionArea><placeName><region type="region" nuts="2">Région Bretagne</region></placeName><orgName type="university">Université de Tunis - El Manar</orgName></affiliation></author><author><name sortKey="Hamrouni, Kamel" sort="Hamrouni, Kamel" uniqKey="Hamrouni K" first="Kamel" last="Hamrouni">Kamel Hamrouni</name><affiliation wicri:level="4"><nlm:affiliation>Université de Tunis El Manar, Ecole Nationale d'Ingnieurs de Tunis, LR-Signal Image et Technologies de l'Information, Tunis 1002, Tunisie. Electronic address: kamel.hamrouni@gmail.com.</nlm:affiliation><country xml:lang="fr">Tunisie</country><wicri:regionArea>Université de Tunis El Manar, Ecole Nationale d'Ingnieurs de Tunis, LR-Signal Image et Technologies de l'Information, Tunis 1002</wicri:regionArea><placeName><settlement type="city">Tunis</settlement><region nuts="2">Gouvernorat de Tunis</region></placeName><orgName type="university">Université de Tunis - El Manar</orgName><placeName><settlement type="city">Tunis</settlement><region type="region" nuts="2">Gouvernorat de Tunis</region></placeName></affiliation></author><author><name sortKey="Solaiman, Basel" sort="Solaiman, Basel" uniqKey="Solaiman B" first="Basel" last="Solaiman">Basel Solaiman</name><affiliation wicri:level="3"><nlm:affiliation>IMT Atlantique, ITI Laboratory, Brest 29238, France. Electronic address: basel.solaiman@telecom-bretagne.eu.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>IMT Atlantique, ITI Laboratory, Brest 29238</wicri:regionArea><placeName><region type="region" nuts="2">Région Bretagne</region></placeName></affiliation></author><author><name sortKey="Boussetta, Sana" sort="Boussetta, Sana" uniqKey="Boussetta S" first="Sana" last="Boussetta">Sana Boussetta</name><affiliation wicri:level="1"><nlm:affiliation>Regional hospital of Ben Arous, Tunisia. Electronic address: sana_boussetta@yahoo.fr.</nlm:affiliation><country xml:lang="fr">Tunisie</country><wicri:regionArea>Regional hospital of Ben Arous</wicri:regionArea></affiliation></author></analytic><series><title level="j">Computer methods and programs in biomedicine</title><idno type="eISSN">1872-7565</idno><imprint><date when="2018" type="published">2018</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Breast Neoplasms (diagnostic imaging)</term><term>Databases, Factual (statistics & numerical data)</term><term>Diagnosis, Computer-Assisted (methods)</term><term>Diagnosis, Computer-Assisted (statistics & numerical data)</term><term>Female (MeSH)</term><term>Fuzzy Logic (MeSH)</term><term>Humans (MeSH)</term><term>Mammography (methods)</term><term>Mammography (statistics & numerical data)</term><term>Radiographic Image Interpretation, Computer-Assisted (methods)</term><term>Radiographic Image Interpretation, Computer-Assisted (statistics & numerical data)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Bases de données factuelles (statistiques et données numériques)</term><term>Diagnostic assisté par ordinateur (méthodes)</term><term>Diagnostic assisté par ordinateur (statistiques et données numériques)</term><term>Femelle (MeSH)</term><term>Humains (MeSH)</term><term>Interprétation d'images radiographiques assistée par ordinateur (méthodes)</term><term>Interprétation d'images radiographiques assistée par ordinateur (statistiques et données numériques)</term><term>Logique floue (MeSH)</term><term>Mammographie (méthodes)</term><term>Mammographie (statistiques et données numériques)</term><term>Tumeurs du sein (imagerie diagnostique)</term></keywords><keywords scheme="MESH" qualifier="diagnostic imaging" xml:lang="en"><term>Breast Neoplasms</term></keywords><keywords scheme="MESH" qualifier="imagerie diagnostique" xml:lang="fr"><term>Tumeurs du sein</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Diagnosis, Computer-Assisted</term><term>Mammography</term><term>Radiographic Image Interpretation, Computer-Assisted</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Diagnostic assisté par ordinateur</term><term>Interprétation d'images radiographiques assistée par ordinateur</term><term>Mammographie</term></keywords><keywords scheme="MESH" qualifier="statistics & numerical data" xml:lang="en"><term>Databases, Factual</term><term>Diagnosis, Computer-Assisted</term><term>Mammography</term><term>Radiographic Image Interpretation, Computer-Assisted</term></keywords><keywords scheme="MESH" qualifier="statistiques et données numériques" xml:lang="fr"><term>Bases de données factuelles</term><term>Diagnostic assisté par ordinateur</term><term>Interprétation d'images radiographiques assistée par ordinateur</term><term>Mammographie</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Female</term><term>Fuzzy Logic</term><term>Humans</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Femelle</term><term>Humains</term><term>Logique floue</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p><b>BACKGROUND AND OBJECTIVE</b></p><p>Accurate mass segmentation in mammographic images is a critical requirement for computer-aided diagnosis systems since it allows accurate feature extraction and thus improves classification precision.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>In this paper, a novel automatic breast mass segmentation approach is presented. This approach consists of mainly three stages: contour initialization applied to a given region of interest; construction of fuzzy contours and estimation of fuzzy membership maps of different classes in the considered image; integration of these maps in the Chan-Vese model to get a fuzzy-energy based model that is used for final delineation of mass.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>The proposed approach is evaluated using mass regions of interest extracted from the mini-MIAS database. The experimental results show that the proposed method achieves an average true positive rate of 91.12% with a precision of 88.08%.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b></p><p>The achieved results show high accuracy in breast mass segmentation when compared to manually annotated ground truth and to other methods from the literature.</p></div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">30195421</PMID><DateCompleted><Year>2019</Year><Month>01</Month><Day>07</Day></DateCompleted><DateRevised><Year>2019</Year><Month>12</Month><Day>10</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1872-7565</ISSN><JournalIssue CitedMedium="Internet"><Volume>164</Volume><PubDate><Year>2018</Year><Month>Oct</Month></PubDate></JournalIssue><Title>Computer methods and programs in biomedicine</Title><ISOAbbreviation>Comput Methods Programs Biomed</ISOAbbreviation></Journal><ArticleTitle>Mammographic mass segmentation using fuzzy contours.</ArticleTitle><Pagination><MedlinePgn>131-142</MedlinePgn></Pagination><ELocationID EIdType="pii" ValidYN="Y">S0169-2607(17)30396-6</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.cmpb.2018.07.005</ELocationID><Abstract><AbstractText Label="BACKGROUND AND OBJECTIVE" NlmCategory="OBJECTIVE">Accurate mass segmentation in mammographic images is a critical requirement for computer-aided diagnosis systems since it allows accurate feature extraction and thus improves classification precision.</AbstractText><AbstractText Label="METHODS" NlmCategory="METHODS">In this paper, a novel automatic breast mass segmentation approach is presented. This approach consists of mainly three stages: contour initialization applied to a given region of interest; construction of fuzzy contours and estimation of fuzzy membership maps of different classes in the considered image; integration of these maps in the Chan-Vese model to get a fuzzy-energy based model that is used for final delineation of mass.</AbstractText><AbstractText Label="RESULTS" NlmCategory="RESULTS">The proposed approach is evaluated using mass regions of interest extracted from the mini-MIAS database. The experimental results show that the proposed method achieves an average true positive rate of 91.12% with a precision of 88.08%.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">The achieved results show high accuracy in breast mass segmentation when compared to manually annotated ground truth and to other methods from the literature.</AbstractText><CopyrightInformation>Copyright © 2018 Elsevier B.V. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Hmida</LastName><ForeName>Marwa</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Université de Tunis El Manar, Ecole Nationale d'Ingnieurs de Tunis, LR-Signal Image et Technologies de l'Information, Tunis 1002, Tunisie; IMT Atlantique, ITI Laboratory, Brest 29238, France. Electronic address: marwa.hmida@telecom-bretagne.eu.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Hamrouni</LastName><ForeName>Kamel</ForeName><Initials>K</Initials><AffiliationInfo><Affiliation>Université de Tunis El Manar, Ecole Nationale d'Ingnieurs de Tunis, LR-Signal Image et Technologies de l'Information, Tunis 1002, Tunisie. Electronic address: kamel.hamrouni@gmail.com.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Solaiman</LastName><ForeName>Basel</ForeName><Initials>B</Initials><AffiliationInfo><Affiliation>IMT Atlantique, ITI Laboratory, Brest 29238, France. Electronic address: basel.solaiman@telecom-bretagne.eu.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Boussetta</LastName><ForeName>Sana</ForeName><Initials>S</Initials><AffiliationInfo><Affiliation>Regional hospital of Ben Arous, Tunisia. Electronic address: sana_boussetta@yahoo.fr.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D023362">Evaluation Study</PublicationType><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2018</Year><Month>07</Month><Day>18</Day></ArticleDate></Article><MedlineJournalInfo><Country>Ireland</Country><MedlineTA>Comput Methods Programs Biomed</MedlineTA><NlmUniqueID>8506513</NlmUniqueID><ISSNLinking>0169-2607</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D001943" MajorTopicYN="N">Breast Neoplasms</DescriptorName><QualifierName UI="Q000000981" MajorTopicYN="Y">diagnostic imaging</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D016208" MajorTopicYN="N">Databases, Factual</DescriptorName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D003936" MajorTopicYN="N">Diagnosis, Computer-Assisted</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D017143" MajorTopicYN="N">Fuzzy Logic</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008327" MajorTopicYN="N">Mammography</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D011857" MajorTopicYN="N">Radiographic Image Interpretation, Computer-Assisted</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName><QualifierName UI="Q000706" MajorTopicYN="N">statistics & numerical data</QualifierName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Active contours</Keyword><Keyword MajorTopicYN="N">Fuzzy contours</Keyword><Keyword MajorTopicYN="N">Mammography</Keyword><Keyword MajorTopicYN="N">Mass segmentation</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2017</Year><Month>03</Month><Day>29</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2018</Year><Month>06</Month><Day>15</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2018</Year><Month>07</Month><Day>16</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2018</Year><Month>9</Month><Day>10</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2018</Year><Month>9</Month><Day>10</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2019</Year><Month>1</Month><Day>8</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">30195421</ArticleId><ArticleId IdType="pii">S0169-2607(17)30396-6</ArticleId><ArticleId IdType="doi">10.1016/j.cmpb.2018.07.005</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>France</li><li>Tunisie</li></country><region><li>Gouvernorat de Tunis</li><li>Région Bretagne</li></region><settlement><li>Tunis</li></settlement><orgName><li>Université de Tunis - El Manar</li></orgName></list><tree><country name="France"><region name="Région Bretagne"><name sortKey="Hmida, Marwa" sort="Hmida, Marwa" uniqKey="Hmida M" first="Marwa" last="Hmida">Marwa Hmida</name></region><name sortKey="Solaiman, Basel" sort="Solaiman, Basel" uniqKey="Solaiman B" first="Basel" last="Solaiman">Basel Solaiman</name></country><country name="Tunisie"><region name="Gouvernorat de Tunis"><name sortKey="Hamrouni, Kamel" sort="Hamrouni, Kamel" uniqKey="Hamrouni K" first="Kamel" last="Hamrouni">Kamel Hamrouni</name></region><name sortKey="Boussetta, Sana" sort="Boussetta, Sana" uniqKey="Boussetta S" first="Sana" last="Boussetta">Sana Boussetta</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Sante/explor/MaghrebDataLibMedV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000339 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000339 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien
|wiki= Sante
|area= MaghrebDataLibMedV1
|flux= Main
|étape= Exploration
|type= RBID
|clé= pubmed:30195421
|texte= Mammographic mass segmentation using fuzzy contours.
}}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Exploration/RBID.i -Sk "pubmed:30195421" \
| HfdSelect -Kh $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd \
| NlmPubMed2Wicri -a MaghrebDataLibMedV1
| This area was generated with Dilib version V0.6.38. |  |