Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge
Identifieur interne : 001B43 ( Pmc/Checkpoint ); précédent : 001B42; suivant : 001B44Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge
Auteurs : Geert Litjens [Pays-Bas] ; Robert Toth [États-Unis] ; Wendy Van De Ven [Pays-Bas] ; Caroline Hoeks [Pays-Bas] ; Sjoerd Kerkstra [Pays-Bas] ; Bram Van Ginneken [Pays-Bas] ; Graham Vincent [Royaume-Uni] ; Gwenael Guillard [Royaume-Uni] ; Neil Birbeck [États-Unis] ; Jindang Zhang [États-Unis] ; Robin Strand [Suède] ; Filip Malmberg [Suède] ; Yangming Ou [États-Unis] ; Christos Davatzikos [États-Unis] ; Matthias Kirschner [Allemagne] ; Florian Jung [Allemagne] ; Jing Yuan [Canada] ; Wu Qiu [Canada] ; Qinquan Gao [Royaume-Uni] ; Philip Ddie Edwards [Royaume-Uni] ; Bianca Maan [Pays-Bas] ; Ferdinand Van Der Heijden [Pays-Bas] ; Soumya Ghose [Australie, France, Espagne] ; Jhimli Mitra [Australie, France, Espagne] ; Jason Dowling [Australie] ; Dean Barratt [Royaume-Uni] ; Henkjan Huisman [Pays-Bas] ; Anant Madabhushi [États-Unis]Source :
- Medical image analysis [ 1361-8415 ] ; 2013.
Abstract
Prostate MRI image segmentation has been an area of intense research due to the increased use of MRI as a modality for the clinical workup of prostate cancer. Segmentation is useful for various tasks, e.g. to accurately localize prostate boundaries for radiotherapy or to initialize multi-modal registration algorithms. In the past, it has been difficult for research groups to evaluate prostate segmentation algorithms on multi-center, multi-vendor and multi-protocol data. Especially because we are dealing with MR images, image appearance, resolution and the presence of artifacts are affected by differences in scanners and/or protocols, which in turn can have a large influence on algorithm accuracy. The Prostate MR Image Segmentation (PROMISE12) challenge was setup to allow a fair and meaningful comparison of segmentation methods on the basis of performance and robustness. In this work we will discuss the initial results of the online PROMISE12 challenge, and the results obtained in the live challenge workshop hosted by the MICCAI2012 conference. In the challenge, 100 prostate MR cases from 4 different centers were included, with differences in scanner manufacturer, field strength and protocol. A total of 11 teams from academic research groups and industry participated. Algorithms showed a wide variety in methods and implementation, including active appearance models, atlas registration and level sets. Evaluation was performed using boundary and volume based metrics which were combined into a single score relating the metrics to human expert performance. The winners of the challenge where the algorithms by teams Imorphics and ScrAutoProstate, with scores of 85.72 and 84.29 overall. Both algorithms where significantly better than all other algorithms in the challenge (
Url:
DOI: 10.1016/j.media.2013.12.002
PubMed: 24418598
PubMed Central: 4137968
Affiliations:
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PMC:4137968Le document en format XML
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<author><name sortKey="Ou, Yangming" sort="Ou, Yangming" uniqKey="Ou Y" first="Yangming" last="Ou">Yangming Ou</name>
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<author><name sortKey="Davatzikos, Christos" sort="Davatzikos, Christos" uniqKey="Davatzikos C" first="Christos" last="Davatzikos">Christos Davatzikos</name>
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<author><name sortKey="Kirschner, Matthias" sort="Kirschner, Matthias" uniqKey="Kirschner M" first="Matthias" last="Kirschner">Matthias Kirschner</name>
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<author><name sortKey="Jung, Florian" sort="Jung, Florian" uniqKey="Jung F" first="Florian" last="Jung">Florian Jung</name>
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<author><name sortKey="Yuan, Jing" sort="Yuan, Jing" uniqKey="Yuan J" first="Jing" last="Yuan">Jing Yuan</name>
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<author><name sortKey="Qiu, Wu" sort="Qiu, Wu" uniqKey="Qiu W" first="Wu" last="Qiu">Wu Qiu</name>
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<author><name sortKey="Gao, Qinquan" sort="Gao, Qinquan" uniqKey="Gao Q" first="Qinquan" last="Gao">Qinquan Gao</name>
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<author><name sortKey="Edwards, Philip Ddie" sort="Edwards, Philip Ddie" uniqKey="Edwards P" first="Philip Ddie" last="Edwards">Philip Ddie Edwards</name>
<affiliation wicri:level="2"><nlm:aff id="A11">Imperial College London, England</nlm:aff>
<country>Royaume-Uni</country>
<placeName><region type="country">Angleterre</region>
</placeName>
<wicri:cityArea>Imperial College London</wicri:cityArea>
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</author>
<author><name sortKey="Maan, Bianca" sort="Maan, Bianca" uniqKey="Maan B" first="Bianca" last="Maan">Bianca Maan</name>
<affiliation wicri:level="1"><nlm:aff id="A12">University of Twente, The Netherlands</nlm:aff>
<country xml:lang="fr">Pays-Bas</country>
<wicri:regionArea>University of Twente</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="Van Der Heijden, Ferdinand" sort="Van Der Heijden, Ferdinand" uniqKey="Van Der Heijden F" first="Ferdinand" last="Van Der Heijden">Ferdinand Van Der Heijden</name>
<affiliation wicri:level="1"><nlm:aff id="A12">University of Twente, The Netherlands</nlm:aff>
<country xml:lang="fr">Pays-Bas</country>
<wicri:regionArea>University of Twente</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="Ghose, Soumya" sort="Ghose, Soumya" uniqKey="Ghose S" first="Soumya" last="Ghose">Soumya Ghose</name>
<affiliation wicri:level="1"><nlm:aff id="A4">Commonwealth Scientific and Industrial Research Organisation, Australia</nlm:aff>
<country xml:lang="fr">Australie</country>
<wicri:regionArea>Commonwealth Scientific and Industrial Research Organisation</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1"><nlm:aff id="A13">Université de Bourgogne, France</nlm:aff>
<country xml:lang="fr">France</country>
<wicri:regionArea>Université de Bourgogne</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1"><nlm:aff id="A14">Universitat de Girona, Spain</nlm:aff>
<country xml:lang="fr">Espagne</country>
<wicri:regionArea>Universitat de Girona</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="Mitra, Jhimli" sort="Mitra, Jhimli" uniqKey="Mitra J" first="Jhimli" last="Mitra">Jhimli Mitra</name>
<affiliation wicri:level="1"><nlm:aff id="A4">Commonwealth Scientific and Industrial Research Organisation, Australia</nlm:aff>
<country xml:lang="fr">Australie</country>
<wicri:regionArea>Commonwealth Scientific and Industrial Research Organisation</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1"><nlm:aff id="A13">Université de Bourgogne, France</nlm:aff>
<country xml:lang="fr">France</country>
<wicri:regionArea>Université de Bourgogne</wicri:regionArea>
</affiliation>
<affiliation wicri:level="1"><nlm:aff id="A14">Universitat de Girona, Spain</nlm:aff>
<country xml:lang="fr">Espagne</country>
<wicri:regionArea>Universitat de Girona</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="Dowling, Jason" sort="Dowling, Jason" uniqKey="Dowling J" first="Jason" last="Dowling">Jason Dowling</name>
<affiliation wicri:level="1"><nlm:aff id="A4">Commonwealth Scientific and Industrial Research Organisation, Australia</nlm:aff>
<country xml:lang="fr">Australie</country>
<wicri:regionArea>Commonwealth Scientific and Industrial Research Organisation</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="Barratt, Dean" sort="Barratt, Dean" uniqKey="Barratt D" first="Dean" last="Barratt">Dean Barratt</name>
<affiliation wicri:level="2"><nlm:aff id="A3">University College London, England</nlm:aff>
<country>Royaume-Uni</country>
<placeName><region type="country">Angleterre</region>
</placeName>
<wicri:cityArea>University College London</wicri:cityArea>
</affiliation>
</author>
<author><name sortKey="Huisman, Henkjan" sort="Huisman, Henkjan" uniqKey="Huisman H" first="Henkjan" last="Huisman">Henkjan Huisman</name>
<affiliation wicri:level="1"><nlm:aff id="A1">Radboud University Nijmegen Medical Centre, The Netherlands</nlm:aff>
<country xml:lang="fr">Pays-Bas</country>
<wicri:regionArea>Radboud University Nijmegen Medical Centre</wicri:regionArea>
</affiliation>
</author>
<author><name sortKey="Madabhushi, Anant" sort="Madabhushi, Anant" uniqKey="Madabhushi A" first="Anant" last="Madabhushi">Anant Madabhushi</name>
<affiliation wicri:level="1"><nlm:aff id="A2">Case Western Reserve University, USA</nlm:aff>
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Case Western Reserve University</wicri:regionArea>
</affiliation>
</author>
</analytic>
<series><title level="j">Medical image analysis</title>
<idno type="ISSN">1361-8415</idno>
<idno type="eISSN">1361-8423</idno>
<imprint><date when="2013">2013</date>
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<front><div type="abstract" xml:lang="en"><p id="P1">Prostate MRI image segmentation has been an area of intense research due to the increased use of MRI as a modality for the clinical workup of prostate cancer. Segmentation is useful for various tasks, e.g. to accurately localize prostate boundaries for radiotherapy or to initialize multi-modal registration algorithms. In the past, it has been difficult for research groups to evaluate prostate segmentation algorithms on multi-center, multi-vendor and multi-protocol data. Especially because we are dealing with MR images, image appearance, resolution and the presence of artifacts are affected by differences in scanners and/or protocols, which in turn can have a large influence on algorithm accuracy. The Prostate MR Image Segmentation (PROMISE12) challenge was setup to allow a fair and meaningful comparison of segmentation methods on the basis of performance and robustness. In this work we will discuss the initial results of the online PROMISE12 challenge, and the results obtained in the live challenge workshop hosted by the MICCAI2012 conference. In the challenge, 100 prostate MR cases from 4 different centers were included, with differences in scanner manufacturer, field strength and protocol. A total of 11 teams from academic research groups and industry participated. Algorithms showed a wide variety in methods and implementation, including active appearance models, atlas registration and level sets. Evaluation was performed using boundary and volume based metrics which were combined into a single score relating the metrics to human expert performance. The winners of the challenge where the algorithms by teams Imorphics and ScrAutoProstate, with scores of 85.72 and 84.29 overall. Both algorithms where significantly better than all other algorithms in the challenge (<italic>p</italic>
< 0.05) and had an efficient implementation with a run time of 8 minutes and 3 second per case respectively. Overall, active appearance model based approaches seemed to outperform other approaches like multi-atlas registration, both on accuracy and computation time. Although average algorithm performance was good to excellent and the Imorphics algorithm outperformed the second observer on average, we showed that algorithm combination might lead to further improvement, indicating that optimal performance for prostate segmentation is not yet obtained. All results are available online at <ext-link ext-link-type="uri" xlink:href="http://promise12.grand-challenge.org/">http://promise12.grand-challenge.org/</ext-link>
.</p>
</div>
</front>
</TEI>
<pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<pmc-dir>properties manuscript</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-journal-id">9713490</journal-id>
<journal-id journal-id-type="pubmed-jr-id">21159</journal-id>
<journal-id journal-id-type="nlm-ta">Med Image Anal</journal-id>
<journal-id journal-id-type="iso-abbrev">Med Image Anal</journal-id>
<journal-title-group><journal-title>Medical image analysis</journal-title>
</journal-title-group>
<issn pub-type="ppub">1361-8415</issn>
<issn pub-type="epub">1361-8423</issn>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">24418598</article-id>
<article-id pub-id-type="pmc">4137968</article-id>
<article-id pub-id-type="doi">10.1016/j.media.2013.12.002</article-id>
<article-id pub-id-type="manuscript">NIHMS604768</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Article</subject>
</subj-group>
</article-categories>
<title-group><article-title>Evaluation of prostate segmentation algorithms for MRI: the PROMISE12 challenge</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Litjens</surname>
<given-names>Geert</given-names>
</name>
<xref ref-type="aff" rid="A1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Toth</surname>
<given-names>Robert</given-names>
</name>
<xref ref-type="aff" rid="A2">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>van de Ven</surname>
<given-names>Wendy</given-names>
</name>
<xref ref-type="aff" rid="A1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Hoeks</surname>
<given-names>Caroline</given-names>
</name>
<xref ref-type="aff" rid="A1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Kerkstra</surname>
<given-names>Sjoerd</given-names>
</name>
<xref ref-type="aff" rid="A1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>van Ginneken</surname>
<given-names>Bram</given-names>
</name>
<xref ref-type="aff" rid="A1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Vincent</surname>
<given-names>Graham</given-names>
</name>
<xref ref-type="aff" rid="A5">5</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Guillard</surname>
<given-names>Gwenael</given-names>
</name>
<xref ref-type="aff" rid="A5">5</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Birbeck</surname>
<given-names>Neil</given-names>
</name>
<xref ref-type="aff" rid="A6">6</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Zhang</surname>
<given-names>Jindang</given-names>
</name>
<xref ref-type="aff" rid="A6">6</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Strand</surname>
<given-names>Robin</given-names>
</name>
<xref ref-type="aff" rid="A7">7</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Malmberg</surname>
<given-names>Filip</given-names>
</name>
<xref ref-type="aff" rid="A7">7</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Ou</surname>
<given-names>Yangming</given-names>
</name>
<xref ref-type="aff" rid="A8">8</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Davatzikos</surname>
<given-names>Christos</given-names>
</name>
<xref ref-type="aff" rid="A8">8</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Kirschner</surname>
<given-names>Matthias</given-names>
</name>
<xref ref-type="aff" rid="A9">9</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Jung</surname>
<given-names>Florian</given-names>
</name>
<xref ref-type="aff" rid="A9">9</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Yuan</surname>
<given-names>Jing</given-names>
</name>
<xref ref-type="aff" rid="A10">10</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Qiu</surname>
<given-names>Wu</given-names>
</name>
<xref ref-type="aff" rid="A10">10</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Gao</surname>
<given-names>Qinquan</given-names>
</name>
<xref ref-type="aff" rid="A11">11</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Edwards</surname>
<given-names>Philip “Eddie”</given-names>
</name>
<xref ref-type="aff" rid="A11">11</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Maan</surname>
<given-names>Bianca</given-names>
</name>
<xref ref-type="aff" rid="A12">12</xref>
</contrib>
<contrib contrib-type="author"><name><surname>van der Heijden</surname>
<given-names>Ferdinand</given-names>
</name>
<xref ref-type="aff" rid="A12">12</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Ghose</surname>
<given-names>Soumya</given-names>
</name>
<xref ref-type="aff" rid="A4">4</xref>
<xref ref-type="aff" rid="A13">13</xref>
<xref ref-type="aff" rid="A14">14</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Mitra</surname>
<given-names>Jhimli</given-names>
</name>
<xref ref-type="aff" rid="A4">4</xref>
<xref ref-type="aff" rid="A13">13</xref>
<xref ref-type="aff" rid="A14">14</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Dowling</surname>
<given-names>Jason</given-names>
</name>
<xref ref-type="aff" rid="A4">4</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Barratt</surname>
<given-names>Dean</given-names>
</name>
<xref ref-type="aff" rid="A3">3</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Huisman</surname>
<given-names>Henkjan</given-names>
</name>
<xref ref-type="aff" rid="A1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Madabhushi</surname>
<given-names>Anant</given-names>
</name>
<xref ref-type="aff" rid="A2">2</xref>
</contrib>
</contrib-group>
<aff id="A1"><label>1</label>
Radboud University Nijmegen Medical Centre, The Netherlands</aff>
<aff id="A2"><label>2</label>
Case Western Reserve University, USA</aff>
<aff id="A3"><label>3</label>
University College London, England</aff>
<aff id="A4"><label>4</label>
Commonwealth Scientific and Industrial Research Organisation, Australia</aff>
<aff id="A5"><label>5</label>
Imorphics, England</aff>
<aff id="A6"><label>6</label>
Siemens Corporate Research, USA</aff>
<aff id="A7"><label>7</label>
Uppsala University, Sweden</aff>
<aff id="A8"><label>8</label>
University of Pennsylvania, USA</aff>
<aff id="A9"><label>9</label>
Technische Universitat Darmstadt, Germany</aff>
<aff id="A10"><label>10</label>
Robarts Research Institute, Canada</aff>
<aff id="A11"><label>11</label>
Imperial College London, England</aff>
<aff id="A12"><label>12</label>
University of Twente, The Netherlands</aff>
<aff id="A13"><label>13</label>
Université de Bourgogne, France</aff>
<aff id="A14"><label>14</label>
Universitat de Girona, Spain</aff>
<author-notes><corresp id="cor1"><email>g.litjens@rad.umcn.nl</email>
(Geert Litjens), <italic>URL:</italic>
<ext-link ext-link-type="uri" xlink:href="http://www.diagnijmegen.nl">http://www.diagnijmegen.nl</ext-link>
(Geert Litjens)</corresp>
</author-notes>
<pub-date pub-type="nihms-submitted"><day>8</day>
<month>7</month>
<year>2014</year>
</pub-date>
<pub-date pub-type="epub"><day>25</day>
<month>12</month>
<year>2013</year>
</pub-date>
<pub-date pub-type="ppub"><month>2</month>
<year>2014</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>01</day>
<month>2</month>
<year>2015</year>
</pub-date>
<volume>18</volume>
<issue>2</issue>
<fpage>359</fpage>
<lpage>373</lpage>
<pmc-comment>elocation-id from pubmed: 10.1016/j.media.2013.12.002</pmc-comment>
<permissions><copyright-statement>© 2013 Elsevier B.V. All rights reserved.</copyright-statement>
<copyright-year>2013</copyright-year>
</permissions>
<abstract><p id="P1">Prostate MRI image segmentation has been an area of intense research due to the increased use of MRI as a modality for the clinical workup of prostate cancer. Segmentation is useful for various tasks, e.g. to accurately localize prostate boundaries for radiotherapy or to initialize multi-modal registration algorithms. In the past, it has been difficult for research groups to evaluate prostate segmentation algorithms on multi-center, multi-vendor and multi-protocol data. Especially because we are dealing with MR images, image appearance, resolution and the presence of artifacts are affected by differences in scanners and/or protocols, which in turn can have a large influence on algorithm accuracy. The Prostate MR Image Segmentation (PROMISE12) challenge was setup to allow a fair and meaningful comparison of segmentation methods on the basis of performance and robustness. In this work we will discuss the initial results of the online PROMISE12 challenge, and the results obtained in the live challenge workshop hosted by the MICCAI2012 conference. In the challenge, 100 prostate MR cases from 4 different centers were included, with differences in scanner manufacturer, field strength and protocol. A total of 11 teams from academic research groups and industry participated. Algorithms showed a wide variety in methods and implementation, including active appearance models, atlas registration and level sets. Evaluation was performed using boundary and volume based metrics which were combined into a single score relating the metrics to human expert performance. The winners of the challenge where the algorithms by teams Imorphics and ScrAutoProstate, with scores of 85.72 and 84.29 overall. Both algorithms where significantly better than all other algorithms in the challenge (<italic>p</italic>
< 0.05) and had an efficient implementation with a run time of 8 minutes and 3 second per case respectively. Overall, active appearance model based approaches seemed to outperform other approaches like multi-atlas registration, both on accuracy and computation time. Although average algorithm performance was good to excellent and the Imorphics algorithm outperformed the second observer on average, we showed that algorithm combination might lead to further improvement, indicating that optimal performance for prostate segmentation is not yet obtained. All results are available online at <ext-link ext-link-type="uri" xlink:href="http://promise12.grand-challenge.org/">http://promise12.grand-challenge.org/</ext-link>
.</p>
</abstract>
<kwd-group><kwd>segmentation</kwd>
<kwd>prostate</kwd>
<kwd>MRI</kwd>
<kwd>challenge</kwd>
</kwd-group>
</article-meta>
</front>
</pmc>
<affiliations><list><country><li>Allemagne</li>
<li>Australie</li>
<li>Canada</li>
<li>Espagne</li>
<li>France</li>
<li>Pays-Bas</li>
<li>Royaume-Uni</li>
<li>Suède</li>
<li>États-Unis</li>
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<name sortKey="Hoeks, Caroline" sort="Hoeks, Caroline" uniqKey="Hoeks C" first="Caroline" last="Hoeks">Caroline Hoeks</name>
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<name sortKey="Kerkstra, Sjoerd" sort="Kerkstra, Sjoerd" uniqKey="Kerkstra S" first="Sjoerd" last="Kerkstra">Sjoerd Kerkstra</name>
<name sortKey="Maan, Bianca" sort="Maan, Bianca" uniqKey="Maan B" first="Bianca" last="Maan">Bianca Maan</name>
<name sortKey="Van De Ven, Wendy" sort="Van De Ven, Wendy" uniqKey="Van De Ven W" first="Wendy" last="Van De Ven">Wendy Van De Ven</name>
<name sortKey="Van Der Heijden, Ferdinand" sort="Van Der Heijden, Ferdinand" uniqKey="Van Der Heijden F" first="Ferdinand" last="Van Der Heijden">Ferdinand Van Der Heijden</name>
<name sortKey="Van Ginneken, Bram" sort="Van Ginneken, Bram" uniqKey="Van Ginneken B" first="Bram" last="Van Ginneken">Bram Van Ginneken</name>
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<name sortKey="Madabhushi, Anant" sort="Madabhushi, Anant" uniqKey="Madabhushi A" first="Anant" last="Madabhushi">Anant Madabhushi</name>
<name sortKey="Ou, Yangming" sort="Ou, Yangming" uniqKey="Ou Y" first="Yangming" last="Ou">Yangming Ou</name>
<name sortKey="Zhang, Jindang" sort="Zhang, Jindang" uniqKey="Zhang J" first="Jindang" last="Zhang">Jindang Zhang</name>
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<country name="Royaume-Uni"><region name="Angleterre"><name sortKey="Vincent, Graham" sort="Vincent, Graham" uniqKey="Vincent G" first="Graham" last="Vincent">Graham Vincent</name>
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<name sortKey="Barratt, Dean" sort="Barratt, Dean" uniqKey="Barratt D" first="Dean" last="Barratt">Dean Barratt</name>
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<name sortKey="Gao, Qinquan" sort="Gao, Qinquan" uniqKey="Gao Q" first="Qinquan" last="Gao">Qinquan Gao</name>
<name sortKey="Guillard, Gwenael" sort="Guillard, Gwenael" uniqKey="Guillard G" first="Gwenael" last="Guillard">Gwenael Guillard</name>
</country>
<country name="Suède"><noRegion><name sortKey="Strand, Robin" sort="Strand, Robin" uniqKey="Strand R" first="Robin" last="Strand">Robin Strand</name>
</noRegion>
<name sortKey="Malmberg, Filip" sort="Malmberg, Filip" uniqKey="Malmberg F" first="Filip" last="Malmberg">Filip Malmberg</name>
</country>
<country name="Allemagne"><noRegion><name sortKey="Kirschner, Matthias" sort="Kirschner, Matthias" uniqKey="Kirschner M" first="Matthias" last="Kirschner">Matthias Kirschner</name>
</noRegion>
<name sortKey="Jung, Florian" sort="Jung, Florian" uniqKey="Jung F" first="Florian" last="Jung">Florian Jung</name>
</country>
<country name="Canada"><noRegion><name sortKey="Yuan, Jing" sort="Yuan, Jing" uniqKey="Yuan J" first="Jing" last="Yuan">Jing Yuan</name>
</noRegion>
<name sortKey="Qiu, Wu" sort="Qiu, Wu" uniqKey="Qiu W" first="Wu" last="Qiu">Wu Qiu</name>
</country>
<country name="Australie"><noRegion><name sortKey="Ghose, Soumya" sort="Ghose, Soumya" uniqKey="Ghose S" first="Soumya" last="Ghose">Soumya Ghose</name>
</noRegion>
<name sortKey="Dowling, Jason" sort="Dowling, Jason" uniqKey="Dowling J" first="Jason" last="Dowling">Jason Dowling</name>
<name sortKey="Mitra, Jhimli" sort="Mitra, Jhimli" uniqKey="Mitra J" first="Jhimli" last="Mitra">Jhimli Mitra</name>
</country>
<country name="France"><noRegion><name sortKey="Ghose, Soumya" sort="Ghose, Soumya" uniqKey="Ghose S" first="Soumya" last="Ghose">Soumya Ghose</name>
</noRegion>
<name sortKey="Mitra, Jhimli" sort="Mitra, Jhimli" uniqKey="Mitra J" first="Jhimli" last="Mitra">Jhimli Mitra</name>
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<country name="Espagne"><noRegion><name sortKey="Ghose, Soumya" sort="Ghose, Soumya" uniqKey="Ghose S" first="Soumya" last="Ghose">Soumya Ghose</name>
</noRegion>
<name sortKey="Mitra, Jhimli" sort="Mitra, Jhimli" uniqKey="Mitra J" first="Jhimli" last="Mitra">Jhimli Mitra</name>
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