Automatic segmentation of the striatum and globus pallidus using MIST: Multimodal Image Segmentation Tool.
Identifieur interne : 000204 ( PubMed/Curation ); précédent : 000203; suivant : 000205Automatic segmentation of the striatum and globus pallidus using MIST: Multimodal Image Segmentation Tool.
Auteurs : Eelke Visser [Royaume-Uni] ; Max C. Keuken [Pays-Bas] ; Gwenaëlle Douaud [Royaume-Uni] ; Veronique Gaura [France] ; Anne-Catherine Bachoud-Levi [France] ; Philippe Remy [France] ; Birte U. Forstmann [Pays-Bas] ; Mark Jenkinson [Royaume-Uni]Source :
- NeuroImage [ 1095-9572 ] ; 2016.
English descriptors
- KwdEn :
- Adult, Algorithms, Brain Mapping (methods), Corpus Striatum (anatomy & histology), Female, Globus Pallidus (anatomy & histology), Humans, Image Processing, Computer-Assisted (methods), Magnetic Resonance Imaging (methods), Male, Models, Neurological, Neuronavigation (methods), Pattern Recognition, Automated (methods).
- MESH :
- anatomy & histology : Corpus Striatum, Globus Pallidus.
- methods : Brain Mapping, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Neuronavigation, Pattern Recognition, Automated.
- Adult, Algorithms, Female, Humans, Male, Models, Neurological.
Abstract
Accurate segmentation of the subcortical structures is frequently required in neuroimaging studies. Most existing methods use only a T1-weighted MRI volume to segment all supported structures and usually rely on a database of training data. We propose a new method that can use multiple image modalities simultaneously and a single reference segmentation for initialisation, without the need for a manually labelled training set. The method models intensity profiles in multiple images around the boundaries of the structure after nonlinear registration. It is trained using a set of unlabelled training data, which may be the same images that are to be segmented, and it can automatically infer the location of the physical boundary using user-specified priors. We show that the method produces high-quality segmentations of the striatum, which is clearly visible on T1-weighted scans, and the globus pallidus, which has poor contrast on such scans. The method compares favourably to existing methods, showing greater overlap with manual segmentations and better consistency.
DOI: 10.1016/j.neuroimage.2015.10.013
PubMed: 26477650
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Electronic address: eelke.visser@ndcn.ox.ac.uk.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford</wicri:regionArea></affiliation></author><author><name sortKey="Keuken, Max C" sort="Keuken, Max C" uniqKey="Keuken M" first="Max C" last="Keuken">Max C. Keuken</name><affiliation wicri:level="1"><nlm:affiliation>Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands.</nlm:affiliation><country xml:lang="fr">Pays-Bas</country><wicri:regionArea>Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam</wicri:regionArea></affiliation></author><author><name sortKey="Douaud, Gwenaelle" sort="Douaud, Gwenaelle" uniqKey="Douaud G" first="Gwenaëlle" last="Douaud">Gwenaëlle Douaud</name><affiliation wicri:level="1"><nlm:affiliation>FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford</wicri:regionArea></affiliation></author><author><name sortKey="Gaura, Veronique" sort="Gaura, Veronique" uniqKey="Gaura V" first="Veronique" last="Gaura">Veronique Gaura</name><affiliation wicri:level="1"><nlm:affiliation>Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Département des Sciences du Vivant (DSV), Institut d'Imagerie Biomédicale (I2BM), MIRCen, F-92260 Fontenay-aux-Roses, France; Centre National de la Recherche Scientifique (CNRS), Université Paris-Sud, Université Paris-Saclay, UMR 9199, Neurodegenerative Diseases Laboratory, F-92260 Fontenay-aux-Roses, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Département des Sciences du Vivant (DSV), Institut d'Imagerie Biomédicale (I2BM), MIRCen, F-92260 Fontenay-aux-Roses, France; Centre National de la Recherche Scientifique (CNRS), Université Paris-Sud, Université Paris-Saclay, UMR 9199, Neurodegenerative Diseases Laboratory, F-92260 Fontenay-aux-Roses</wicri:regionArea></affiliation></author><author><name sortKey="Bachoud Levi, Anne Catherine" sort="Bachoud Levi, Anne Catherine" uniqKey="Bachoud Levi A" first="Anne-Catherine" last="Bachoud-Levi">Anne-Catherine Bachoud-Levi</name><affiliation wicri:level="1"><nlm:affiliation>AP-HP, Hôpital Henri Mondor, Centre de Référence-Maladie de Huntington, Neurologie cognitive, Créteil, France; Université Paris Est, Faculté de médecine, Créteil, France; INSERM U955, Equipe 01, Neuropsychologie Interventionnelle, Créteil, France; Département d'Etudes Cognitives, Ecole Normale Supérieure, PSL Research University, Paris, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>AP-HP, Hôpital Henri Mondor, Centre de Référence-Maladie de Huntington, Neurologie cognitive, Créteil, France; Université Paris Est, Faculté de médecine, Créteil, France; INSERM U955, Equipe 01, Neuropsychologie Interventionnelle, Créteil, France; Département d'Etudes Cognitives, Ecole Normale Supérieure, PSL Research University, Paris</wicri:regionArea></affiliation></author><author><name sortKey="Remy, Philippe" sort="Remy, Philippe" uniqKey="Remy P" first="Philippe" last="Remy">Philippe Remy</name><affiliation wicri:level="1"><nlm:affiliation>Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Département des Sciences du Vivant (DSV), Institut d'Imagerie Biomédicale (I2BM), MIRCen, F-92260 Fontenay-aux-Roses, France; Centre Expert Parkinson et NEURATRIS, CHU Henri Mondor, Pôle Neuro-Locomoteur, Assistance Publique Hôpitaux de Paris et Université Paris Est Créteil, France.</nlm:affiliation><country xml:lang="fr">France</country><wicri:regionArea>Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Département des Sciences du Vivant (DSV), Institut d'Imagerie Biomédicale (I2BM), MIRCen, F-92260 Fontenay-aux-Roses, France; Centre Expert Parkinson et NEURATRIS, CHU Henri Mondor, Pôle Neuro-Locomoteur, Assistance Publique Hôpitaux de Paris et Université Paris Est Créteil</wicri:regionArea></affiliation></author><author><name sortKey="Forstmann, Birte U" sort="Forstmann, Birte U" uniqKey="Forstmann B" first="Birte U" last="Forstmann">Birte U. Forstmann</name><affiliation wicri:level="1"><nlm:affiliation>Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands.</nlm:affiliation><country xml:lang="fr">Pays-Bas</country><wicri:regionArea>Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam</wicri:regionArea></affiliation></author><author><name sortKey="Jenkinson, Mark" sort="Jenkinson, Mark" uniqKey="Jenkinson M" first="Mark" last="Jenkinson">Mark Jenkinson</name><affiliation wicri:level="1"><nlm:affiliation>FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford</wicri:regionArea></affiliation></author></analytic><series><title level="j">NeuroImage</title><idno type="eISSN">1095-9572</idno><imprint><date when="2016" type="published">2016</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult</term><term>Algorithms</term><term>Brain Mapping (methods)</term><term>Corpus Striatum (anatomy & histology)</term><term>Female</term><term>Globus Pallidus (anatomy & histology)</term><term>Humans</term><term>Image Processing, Computer-Assisted (methods)</term><term>Magnetic Resonance Imaging (methods)</term><term>Male</term><term>Models, Neurological</term><term>Neuronavigation (methods)</term><term>Pattern Recognition, Automated (methods)</term></keywords><keywords scheme="MESH" qualifier="anatomy & histology" xml:lang="en"><term>Corpus Striatum</term><term>Globus Pallidus</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Brain Mapping</term><term>Image Processing, Computer-Assisted</term><term>Magnetic Resonance Imaging</term><term>Neuronavigation</term><term>Pattern Recognition, Automated</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adult</term><term>Algorithms</term><term>Female</term><term>Humans</term><term>Male</term><term>Models, Neurological</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Accurate segmentation of the subcortical structures is frequently required in neuroimaging studies. Most existing methods use only a T1-weighted MRI volume to segment all supported structures and usually rely on a database of training data. We propose a new method that can use multiple image modalities simultaneously and a single reference segmentation for initialisation, without the need for a manually labelled training set. The method models intensity profiles in multiple images around the boundaries of the structure after nonlinear registration. It is trained using a set of unlabelled training data, which may be the same images that are to be segmented, and it can automatically infer the location of the physical boundary using user-specified priors. We show that the method produces high-quality segmentations of the striatum, which is clearly visible on T1-weighted scans, and the globus pallidus, which has poor contrast on such scans. The method compares favourably to existing methods, showing greater overlap with manual segmentations and better consistency.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">26477650</PMID><DateCreated><Year>2015</Year><Month>12</Month><Day>25</Day></DateCreated><DateCompleted><Year>2016</Year><Month>09</Month><Day>30</Day></DateCompleted><DateRevised><Year>2016</Year><Month>11</Month><Day>22</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1095-9572</ISSN><JournalIssue CitedMedium="Internet"><Volume>125</Volume><PubDate><Year>2016</Year><Month>Jan</Month><Day>15</Day></PubDate></JournalIssue><Title>NeuroImage</Title><ISOAbbreviation>Neuroimage</ISOAbbreviation></Journal><ArticleTitle>Automatic segmentation of the striatum and globus pallidus using MIST: Multimodal Image Segmentation Tool.</ArticleTitle><Pagination><MedlinePgn>479-97</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.neuroimage.2015.10.013</ELocationID><ELocationID EIdType="pii" ValidYN="Y">S1053-8119(15)00914-3</ELocationID><Abstract><AbstractText>Accurate segmentation of the subcortical structures is frequently required in neuroimaging studies. Most existing methods use only a T1-weighted MRI volume to segment all supported structures and usually rely on a database of training data. We propose a new method that can use multiple image modalities simultaneously and a single reference segmentation for initialisation, without the need for a manually labelled training set. The method models intensity profiles in multiple images around the boundaries of the structure after nonlinear registration. It is trained using a set of unlabelled training data, which may be the same images that are to be segmented, and it can automatically infer the location of the physical boundary using user-specified priors. We show that the method produces high-quality segmentations of the striatum, which is clearly visible on T1-weighted scans, and the globus pallidus, which has poor contrast on such scans. The method compares favourably to existing methods, showing greater overlap with manual segmentations and better consistency.</AbstractText><CopyrightInformation>Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Visser</LastName><ForeName>Eelke</ForeName><Initials>E</Initials><AffiliationInfo><Affiliation>FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom. Electronic address: eelke.visser@ndcn.ox.ac.uk.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Keuken</LastName><ForeName>Max C</ForeName><Initials>MC</Initials><AffiliationInfo><Affiliation>Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Douaud</LastName><ForeName>Gwenaëlle</ForeName><Initials>G</Initials><AffiliationInfo><Affiliation>FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gaura</LastName><ForeName>Veronique</ForeName><Initials>V</Initials><AffiliationInfo><Affiliation>Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Département des Sciences du Vivant (DSV), Institut d'Imagerie Biomédicale (I2BM), MIRCen, F-92260 Fontenay-aux-Roses, France; Centre National de la Recherche Scientifique (CNRS), Université Paris-Sud, Université Paris-Saclay, UMR 9199, Neurodegenerative Diseases Laboratory, F-92260 Fontenay-aux-Roses, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Bachoud-Levi</LastName><ForeName>Anne-Catherine</ForeName><Initials>AC</Initials><AffiliationInfo><Affiliation>AP-HP, Hôpital Henri Mondor, Centre de Référence-Maladie de Huntington, Neurologie cognitive, Créteil, France; Université Paris Est, Faculté de médecine, Créteil, France; INSERM U955, Equipe 01, Neuropsychologie Interventionnelle, Créteil, France; Département d'Etudes Cognitives, Ecole Normale Supérieure, PSL Research University, Paris, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Remy</LastName><ForeName>Philippe</ForeName><Initials>P</Initials><AffiliationInfo><Affiliation>Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Département des Sciences du Vivant (DSV), Institut d'Imagerie Biomédicale (I2BM), MIRCen, F-92260 Fontenay-aux-Roses, France; Centre Expert Parkinson et NEURATRIS, CHU Henri Mondor, Pôle Neuro-Locomoteur, Assistance Publique Hôpitaux de Paris et Université Paris Est Créteil, France.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Forstmann</LastName><ForeName>Birte U</ForeName><Initials>BU</Initials><AffiliationInfo><Affiliation>Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jenkinson</LastName><ForeName>Mark</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>FMRIB Centre, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>098369</GrantID><Agency>Wellcome Trust</Agency><Country>United Kingdom</Country></Grant><Grant><GrantID>G0700399</GrantID><Agency>Medical Research Council</Agency><Country>United Kingdom</Country></Grant><Grant><GrantID>MR/K006673/1</GrantID><Agency>Medical Research Council</Agency><Country>United Kingdom</Country></Grant><Grant><GrantID>U54 MH091657</GrantID><Acronym>MH</Acronym><Agency>NIMH NIH HHS</Agency><Country>United States</Country></Grant><Grant><GrantID>098369/Z/12/Z</GrantID><Agency>Wellcome Trust</Agency><Country>United Kingdom</Country></Grant><Grant><GrantID>1U54MH091657</GrantID><Acronym>MH</Acronym><Agency>NIMH NIH HHS</Agency><Country>United States</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D052061">Research Support, N.I.H., Extramural</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2015</Year><Month>10</Month><Day>19</Day></ArticleDate></Article><MedlineJournalInfo><Country>United 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MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D008959" MajorTopicYN="Y">Models, Neurological</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D038361" MajorTopicYN="N">Neuronavigation</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D010363" MajorTopicYN="N">Pattern Recognition, Automated</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="N">methods</QualifierName></MeshHeading></MeshHeadingList><OtherID Source="NLM">PMC4692519</OtherID><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Brain</Keyword><Keyword MajorTopicYN="N">Globus pallidus</Keyword><Keyword MajorTopicYN="N">Huntington</Keyword><Keyword MajorTopicYN="N">Multimodal</Keyword><Keyword MajorTopicYN="N">Segmentation</Keyword><Keyword MajorTopicYN="N">Striatum</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2015</Year><Month>02</Month><Day>20</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2015</Year><Month>10</Month><Day>05</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2015</Year><Month>10</Month><Day>06</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2015</Year><Month>10</Month><Day>20</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2015</Year><Month>10</Month><Day>20</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2016</Year><Month>10</Month><Day>1</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">26477650</ArticleId><ArticleId IdType="pii">S1053-8119(15)00914-3</ArticleId><ArticleId 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