<?xml version="1.0" encoding="utf-8"?>
<TEI xmlns="http://www.tei-c.org/ns/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:hal="http://hal.archives-ouvertes.fr/" xmlns:gml="http://www.opengis.net/gml/3.3/" xmlns:gmlce="http://www.opengis.net/gml/3.3/ce" version="1.1" xsi:schemaLocation="http://www.tei-c.org/ns/1.0 http://api.archives-ouvertes.fr/documents/aofr-sword.xsd">
  <teiHeader>
    <fileDesc>
      <titleStmt>
        <title>HAL TEI export of hal-03883749</title>
      </titleStmt>
      <publicationStmt>
        <distributor>CCSD</distributor>
        <availability status="restricted">
          <licence target="https://creativecommons.org/publicdomain/zero/1.0/">CC0 1.0 - Universal</licence>
        </availability>
        <date when="2026-05-16T10:25:16+02:00"/>
      </publicationStmt>
      <sourceDesc>
        <p part="N">HAL API Platform</p>
      </sourceDesc>
    </fileDesc>
  </teiHeader>
  <text>
    <body>
      <listBibl>
        <biblFull>
          <titleStmt>
            <title xml:lang="en">Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can trust</title>
            <author role="aut">
              <persName>
                <forename type="first">Benjamin</forename>
                <surname>Lambert</surname>
              </persName>
              <idno type="halauthorid">1216644-0</idno>
              <affiliation ref="#struct-408885"/>
              <affiliation ref="#struct-476333"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Florence</forename>
                <surname>Forbes</surname>
              </persName>
              <email type="md5">60bdfbf9919b7f5995fcbfffb65ec34f</email>
              <email type="domain">inrialpes.fr</email>
              <idno type="idhal" notation="string">florence-forbes</idno>
              <idno type="idhal" notation="numeric">16305</idno>
              <idno type="halauthorid" notation="string">998-16305</idno>
              <idno type="ORCID">https://orcid.org/0000-0003-3639-0226</idno>
              <idno type="IDREF">https://www.idref.fr/12469781X</idno>
              <affiliation ref="#struct-1043080"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Senan</forename>
                <surname>Doyle</surname>
              </persName>
              <idno type="halauthorid">545462-0</idno>
              <affiliation ref="#struct-476333"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Alan</forename>
                <surname>Tucholka</surname>
              </persName>
              <idno type="halauthorid">361158-0</idno>
              <affiliation ref="#struct-476333"/>
            </author>
            <author role="aut">
              <persName>
                <forename type="first">Michel</forename>
                <surname>Dojat</surname>
              </persName>
              <email type="md5">08abfe57ff512b8bb72378ecb6ca4796</email>
              <email type="domain">univ-grenoble-alpes.fr</email>
              <idno type="idhal" notation="string">michel-dojat</idno>
              <idno type="idhal" notation="numeric">1720</idno>
              <idno type="halauthorid" notation="string">3949-1720</idno>
              <idno type="RESEARCHERID">http://www.researcherid.com/rid/G-7758-2011</idno>
              <idno type="ORCID">https://orcid.org/0000-0003-2747-6845</idno>
              <idno type="IDREF">https://www.idref.fr/075440202</idno>
              <idno type="RESEARCHERID">http://www.researcherid.com/rid/http://www.researcherid.com/rid/G-7758-2011</idno>
              <affiliation ref="#struct-408885"/>
            </author>
            <editor role="depositor">
              <persName>
                <forename>Florence</forename>
                <surname>Forbes</surname>
              </persName>
              <email type="md5">aa8c9e68e96151a3e4bd20ced86c1298</email>
              <email type="domain">inria.fr</email>
            </editor>
          </titleStmt>
          <editionStmt>
            <edition n="v1" type="current">
              <date type="whenSubmitted">2022-12-04 11:36:18</date>
              <date type="whenModified">2025-09-27 18:47:16</date>
              <date type="whenReleased">2022-12-05 08:52:42</date>
              <date type="whenProduced">2022-09-18</date>
              <date type="whenEndEmbargoed">2022-12-04</date>
              <ref type="file" target="https://hal.science/hal-03883749v1/document">
                <date notBefore="2022-12-04"/>
              </ref>
              <ref type="file" subtype="author" n="1" target="https://hal.science/hal-03883749v1/file/MICCAI_2022_Paper_HD-final.pdf" id="file-3883749-3397291">
                <date notBefore="2022-12-04"/>
              </ref>
            </edition>
            <respStmt>
              <resp>contributor</resp>
              <name key="160528">
                <persName>
                  <forename>Florence</forename>
                  <surname>Forbes</surname>
                </persName>
                <email type="md5">aa8c9e68e96151a3e4bd20ced86c1298</email>
                <email type="domain">inria.fr</email>
              </name>
            </respStmt>
          </editionStmt>
          <publicationStmt>
            <distributor>CCSD</distributor>
            <idno type="halId">hal-03883749</idno>
            <idno type="halUri">https://hal.science/hal-03883749</idno>
            <idno type="halBibtex">lambert:hal-03883749</idno>
            <idno type="halRefHtml">&lt;i&gt;iMIMIC 2022 - Workshop on Interpretability of Machine Intelligence in Medical Image Computing&lt;/i&gt;, Sep 2022, Singapore, Singapore. pp.61-70, &lt;a target="_blank" href="https://dx.doi.org/10.1007/978-3-031-17976-1_6"&gt;&amp;#x27E8;10.1007/978-3-031-17976-1_6&amp;#x27E9;&lt;/a&gt;</idno>
            <idno type="halRef">iMIMIC 2022 - Workshop on Interpretability of Machine Intelligence in Medical Image Computing, Sep 2022, Singapore, Singapore. pp.61-70, &amp;#x27E8;10.1007/978-3-031-17976-1_6&amp;#x27E9;</idno>
            <availability status="restricted">
              <licence target="https://about.hal.science/hal-authorisation-v1/">HAL Authorization<ref corresp="#file-3883749-3397291"/></licence>
            </availability>
          </publicationStmt>
          <seriesStmt>
            <idno type="stamp" n="UGA">HAL Grenoble Alpes</idno>
            <idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno>
            <idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno>
            <idno type="stamp" n="INPG">Institut polytechnique de Grenoble</idno>
            <idno type="stamp" n="INRIA-RHA">INRIA Grenoble - Rhône-Alpes</idno>
            <idno type="stamp" n="INSMI">CNRS-INSMI - INstitut des Sciences Mathématiques et de leurs Interactions</idno>
            <idno type="stamp" n="INRIA_TEST">INRIA - Institut National de Recherche en Informatique et en Automatique</idno>
            <idno type="stamp" n="LJK">Laboratoire Jean Kuntzmann</idno>
            <idno type="stamp" n="LJK_PS" corresp="LJK">Département Probabilités et Statistiques</idno>
            <idno type="stamp" n="TESTALAIN1">TESTALAIN1</idno>
            <idno type="stamp" n="INRIA2">INRIA 2</idno>
            <idno type="stamp" n="INRIA-RENGRE">INRIA-RENGRE</idno>
            <idno type="stamp" n="LJK-PS-STATIFY" corresp="LJK_PS">STATIFY</idno>
            <idno type="stamp" n="UGA-EPE">Université Grenoble Alpes [2020-*]</idno>
            <idno type="stamp" n="GRENOBLEINSTITUTNEUROSCIENCES">Grenoble Institut Neurociences</idno>
            <idno type="stamp" n="TEST-UGA">TEST-UGA</idno>
          </seriesStmt>
          <notesStmt>
            <note type="audience" n="2">International</note>
            <note type="invited" n="0">No</note>
            <note type="popular" n="0">No</note>
            <note type="peer" n="1">Yes</note>
            <note type="proceedings" n="1">Yes</note>
          </notesStmt>
          <sourceDesc>
            <biblStruct>
              <analytic>
                <title xml:lang="en">Beyond Voxel Prediction Uncertainty: Identifying brain lesions you can trust</title>
                <author role="aut">
                  <persName>
                    <forename type="first">Benjamin</forename>
                    <surname>Lambert</surname>
                  </persName>
                  <idno type="halauthorid">1216644-0</idno>
                  <affiliation ref="#struct-408885"/>
                  <affiliation ref="#struct-476333"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Florence</forename>
                    <surname>Forbes</surname>
                  </persName>
                  <email type="md5">60bdfbf9919b7f5995fcbfffb65ec34f</email>
                  <email type="domain">inrialpes.fr</email>
                  <idno type="idhal" notation="string">florence-forbes</idno>
                  <idno type="idhal" notation="numeric">16305</idno>
                  <idno type="halauthorid" notation="string">998-16305</idno>
                  <idno type="ORCID">https://orcid.org/0000-0003-3639-0226</idno>
                  <idno type="IDREF">https://www.idref.fr/12469781X</idno>
                  <affiliation ref="#struct-1043080"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Senan</forename>
                    <surname>Doyle</surname>
                  </persName>
                  <idno type="halauthorid">545462-0</idno>
                  <affiliation ref="#struct-476333"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Alan</forename>
                    <surname>Tucholka</surname>
                  </persName>
                  <idno type="halauthorid">361158-0</idno>
                  <affiliation ref="#struct-476333"/>
                </author>
                <author role="aut">
                  <persName>
                    <forename type="first">Michel</forename>
                    <surname>Dojat</surname>
                  </persName>
                  <email type="md5">08abfe57ff512b8bb72378ecb6ca4796</email>
                  <email type="domain">univ-grenoble-alpes.fr</email>
                  <idno type="idhal" notation="string">michel-dojat</idno>
                  <idno type="idhal" notation="numeric">1720</idno>
                  <idno type="halauthorid" notation="string">3949-1720</idno>
                  <idno type="RESEARCHERID">http://www.researcherid.com/rid/G-7758-2011</idno>
                  <idno type="ORCID">https://orcid.org/0000-0003-2747-6845</idno>
                  <idno type="IDREF">https://www.idref.fr/075440202</idno>
                  <idno type="RESEARCHERID">http://www.researcherid.com/rid/http://www.researcherid.com/rid/G-7758-2011</idno>
                  <affiliation ref="#struct-408885"/>
                </author>
              </analytic>
              <monogr>
                <title level="m">Lecture Notes in Computer Science</title>
                <meeting>
                  <title>iMIMIC 2022 - Workshop on Interpretability of Machine Intelligence in Medical Image Computing</title>
                  <date type="start">2022-09-18</date>
                  <date type="end">2022-09-22</date>
                  <settlement>Singapore</settlement>
                  <country key="SG">Singapore</country>
                </meeting>
                <imprint>
                  <biblScope unit="volume">13611</biblScope>
                  <biblScope unit="pp">61-70</biblScope>
                  <date type="datePub">2022-10-07</date>
                </imprint>
              </monogr>
              <idno type="doi">10.1007/978-3-031-17976-1_6</idno>
            </biblStruct>
          </sourceDesc>
          <profileDesc>
            <langUsage>
              <language ident="en">English</language>
            </langUsage>
            <textClass>
              <keywords scheme="author">
                <term xml:lang="en">MS lesion</term>
                <term xml:lang="en">Detection</term>
                <term xml:lang="en">Deep Learning</term>
                <term xml:lang="en">Interpretabilty</term>
                <term xml:lang="en">Prediction</term>
              </keywords>
              <classCode scheme="halDomain" n="math.math-st">Mathematics [math]/Statistics [math.ST]</classCode>
              <classCode scheme="halTypology" n="COMM">Conference papers</classCode>
              <classCode scheme="halOldTypology" n="COMM">Conference papers</classCode>
              <classCode scheme="halTreeTypology" n="COMM">Conference papers</classCode>
            </textClass>
            <abstract xml:lang="en">
              <p>Deep neural networks have become the gold-standard approach for the automated segmentation of 3D medical images. Their full acceptance by clinicians remains however hampered by the lack of intelligible uncertainty assessment of the provided results. Most approaches to quantify their uncertainty, such as the popular Monte Carlo dropout, restrict to some measure of uncertainty in prediction at the voxel level. In addition not to be clearly related to genuine medical uncertainty, this is not clinically satisfying as most objects of interest (e.g. brain lesions) are made of groups of voxels whose overall relevance may not simply reduce to the sum or mean of their individual uncertainties. In this work, we propose to go beyond voxel-wise assessment using an innovative Graph Neural Network approach, trained from the outputs of a Monte Carlo dropout model. This network allows the fusion of three estimators of voxel uncertainty: entropy, variance, and model's confidence; and can be applied to any lesion, regardless of its shape or size. We demonstrate the superiority of our approach for uncertainty estimate on a task of Multiple Sclerosis lesions segmentation.</p>
            </abstract>
          </profileDesc>
        </biblFull>
      </listBibl>
    </body>
    <back>
      <listOrg type="structures">
        <org type="regrouplaboratory" xml:id="struct-408885" status="VALID">
          <idno type="IdRef">184664446</idno>
          <idno type="ISNI">0000000404293736</idno>
          <idno type="RNSR">200716488W</idno>
          <idno type="ROR">https://ror.org/04as3rk94</idno>
          <orgName>[GIN] Grenoble Institut des Neurosciences</orgName>
          <orgName type="acronym">GIN</orgName>
          <date type="start">2020-01-01</date>
          <desc>
            <address>
              <addrLine>Site Santé - Bâtiment Edmond J. Safra - Chemin Fortuné Ferrini 38706 La Tronche Cedex</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">https://neurosciences.univ-grenoble-alpes.fr/</ref>
          </desc>
          <listRelation>
            <relation name="U1216" active="#struct-303623" type="direct"/>
            <relation active="#struct-1042703" type="direct"/>
          </listRelation>
        </org>
        <org type="institution" xml:id="struct-476333" status="VALID">
          <orgName>Pixyl Medical [Grenoble]</orgName>
          <desc>
            <address>
              <addrLine>655 Avenue de l'Europe38330 Montbonnot-Saint-Martin</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">http://pixylmedical.com/</ref>
          </desc>
        </org>
        <org type="researchteam" xml:id="struct-1043080" status="VALID">
          <idno type="RNSR">202023582A</idno>
          <idno type="ROR">https://ror.org/01nc10f70</idno>
          <orgName>Modèles statistiques bayésiens et des valeurs extrêmes pour données structurées et de grande dimension</orgName>
          <orgName type="acronym">STATIFY</orgName>
          <date type="start">2020-04-01</date>
          <date type="end">2027-12-31</date>
          <desc>
            <address>
              <addrLine>Inovallée 655 avenue de l'Europe 38330 Montbonnot</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">https://team.inria.fr/statify/</ref>
          </desc>
          <listRelation>
            <relation active="#struct-2497" type="direct"/>
            <relation active="#struct-300009" type="indirect"/>
            <relation active="#struct-1043077" type="direct"/>
            <relation name="UMR5224" active="#struct-441569" type="indirect"/>
            <relation active="#struct-1042703" type="indirect"/>
            <relation active="#struct-1043329" type="indirect"/>
          </listRelation>
        </org>
        <org type="institution" xml:id="struct-303623" status="VALID">
          <idno type="IdRef">026388278</idno>
          <idno type="ROR">https://ror.org/02vjkv261</idno>
          <orgName>Institut National de la Santé et de la Recherche Médicale</orgName>
          <orgName type="acronym">INSERM</orgName>
          <desc>
            <address>
              <addrLine>101, rue de Tolbiac, 75013 Paris</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">http://www.inserm.fr</ref>
          </desc>
        </org>
        <org type="regroupinstitution" xml:id="struct-1042703" status="VALID">
          <idno type="IdRef">240648315</idno>
          <idno type="ROR">https://ror.org/02rx3b187</idno>
          <orgName>Université Grenoble Alpes</orgName>
          <orgName type="acronym">UGA</orgName>
          <date type="start">2020-01-01</date>
          <desc>
            <address>
              <addrLine>Adresse CS 40700 - 38058 Grenoble cedex</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">http://www.univ-grenoble-alpes.fr</ref>
          </desc>
        </org>
        <org type="laboratory" xml:id="struct-2497" status="VALID">
          <idno type="RNSR">199218244V</idno>
          <idno type="ROR">https://ror.org/00n8d6z93</idno>
          <orgName>Centre Inria de l'Université Grenoble Alpes</orgName>
          <desc>
            <address>
              <addrLine>Inovallée655 avenue de l'Europe38330 Montbonnot</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">http://www.inria.fr/centre/grenoble</ref>
          </desc>
          <listRelation>
            <relation active="#struct-300009" type="direct"/>
          </listRelation>
        </org>
        <org type="institution" xml:id="struct-300009" status="VALID">
          <idno type="ROR">https://ror.org/02kvxyf05</idno>
          <orgName>Institut National de Recherche en Informatique et en Automatique</orgName>
          <orgName type="acronym">Inria</orgName>
          <desc>
            <address>
              <addrLine>Domaine de VoluceauRocquencourt - BP 10578153 Le Chesnay Cedex</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">http://www.inria.fr/en/</ref>
          </desc>
        </org>
        <org type="laboratory" xml:id="struct-1043077" status="VALID">
          <idno type="IdRef">184945011</idno>
          <idno type="ISNI">0000 0004 0383 676X</idno>
          <idno type="RNSR">200711891Z</idno>
          <idno type="ROR">https://ror.org/04ett5b41</idno>
          <orgName>Laboratoire Jean Kuntzmann</orgName>
          <orgName type="acronym">LJK</orgName>
          <date type="start">2020-01-01</date>
          <desc>
            <address>
              <addrLine>Bâtiment IMAG, CS 40700, F-38058 Grenoble Cedex 9</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">https://ljk.imag.fr/</ref>
          </desc>
          <listRelation>
            <relation active="#struct-300009" type="direct"/>
            <relation name="UMR5224" active="#struct-441569" type="direct"/>
            <relation active="#struct-1042703" type="direct"/>
            <relation active="#struct-1043329" type="direct"/>
          </listRelation>
        </org>
        <org type="regroupinstitution" xml:id="struct-441569" status="VALID">
          <idno type="IdRef">02636817X</idno>
          <idno type="ISNI">0000000122597504</idno>
          <idno type="ROR">https://ror.org/02feahw73</idno>
          <orgName>Centre National de la Recherche Scientifique</orgName>
          <orgName type="acronym">CNRS</orgName>
          <date type="start">1939-10-19</date>
          <desc>
            <address>
              <country key="FR"/>
            </address>
            <ref type="url">https://www.cnrs.fr/</ref>
          </desc>
        </org>
        <org type="institution" xml:id="struct-1043329" status="VALID">
          <idno type="IdRef">026388804</idno>
          <idno type="ROR">https://ror.org/05sbt2524</idno>
          <orgName>Institut polytechnique de Grenoble - Grenoble Institute of Technology</orgName>
          <orgName type="acronym">Grenoble INP</orgName>
          <date type="start">2020-01-01</date>
          <desc>
            <address>
              <addrLine>46 avenue Félix Viallet 38031 Grenoble Cedex 1</addrLine>
              <country key="FR"/>
            </address>
            <ref type="url">http://www.grenoble-inp.fr/</ref>
          </desc>
          <listRelation>
            <relation active="#struct-1042703" type="direct"/>
          </listRelation>
        </org>
      </listOrg>
    </back>
  </text>
</TEI>