000180698 001__ 180698
000180698 005__ 20240229145629.0
000180698 0247_ $$2doi$$a10.1038/s41467-022-30695-9
000180698 0247_ $$2pmid$$apmid:35840566
000180698 0247_ $$2altmetric$$aaltmetric:132652279
000180698 037__ $$aDKFZ-2022-01494
000180698 041__ $$aEnglish
000180698 082__ $$a500
000180698 1001_ $$00000-0002-3005-4523$$aAntonelli, Michela$$b0
000180698 245__ $$aThe Medical Segmentation Decathlon.
000180698 260__ $$a[London]$$bNature Publishing Group UK$$c2022
000180698 3367_ $$2DRIVER$$aarticle
000180698 3367_ $$2DataCite$$aOutput Types/Journal article
000180698 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1658138861_17496
000180698 3367_ $$2BibTeX$$aARTICLE
000180698 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000180698 3367_ $$00$$2EndNote$$aJournal Article
000180698 500__ $$a#EA:E130#LA:E130#
000180698 520__ $$aInternational challenges have become the de facto standard for comparative assessment of image analysis algorithms. Although segmentation is the most widely investigated medical image processing task, the various challenges have been organized to focus only on specific clinical tasks. We organized the Medical Segmentation Decathlon (MSD)-a biomedical image analysis challenge, in which algorithms compete in a multitude of both tasks and modalities to investigate the hypothesis that a method capable of performing well on multiple tasks will generalize well to a previously unseen task and potentially outperform a custom-designed solution. MSD results confirmed this hypothesis, moreover, MSD winner continued generalizing well to a wide range of other clinical problems for the next two years. Three main conclusions can be drawn from this study: (1) state-of-the-art image segmentation algorithms generalize well when retrained on unseen tasks; (2) consistent algorithmic performance across multiple tasks is a strong surrogate of algorithmic generalizability; (3) the training of accurate AI segmentation models is now commoditized to scientists that are not versed in AI model training.
000180698 536__ $$0G:(DE-HGF)POF4-315$$a315 - Bildgebung und Radioonkologie (POF4-315)$$cPOF4-315$$fPOF IV$$x0
000180698 588__ $$aDataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
000180698 7001_ $$0P:(DE-He78)97e904f47dab556a77c0149cd0002591$$aReinke, Annika$$b1$$eFirst author
000180698 7001_ $$00000-0001-8734-6482$$aBakas, Spyridon$$b2
000180698 7001_ $$aFarahani, Keyvan$$b3
000180698 7001_ $$0P:(DE-He78)bb6a7a70f976eb8df1769944bf913596$$aKopp-Schneider, Annette$$b4
000180698 7001_ $$00000-0001-5733-2127$$aLandman, Bennett A$$b5
000180698 7001_ $$00000-0003-1554-1291$$aLitjens, Geert$$b6
000180698 7001_ $$00000-0003-4136-5690$$aMenze, Bjoern$$b7
000180698 7001_ $$aRonneberger, Olaf$$b8
000180698 7001_ $$aSummers, Ronald M$$b9
000180698 7001_ $$avan Ginneken, Bram$$b10
000180698 7001_ $$aBilello, Michel$$b11
000180698 7001_ $$aBilic, Patrick$$b12
000180698 7001_ $$aChrist, Patrick F$$b13
000180698 7001_ $$00000-0002-6554-0310$$aDo, Richard K G$$b14
000180698 7001_ $$aGollub, Marc J$$b15
000180698 7001_ $$aHeckers, Stephan H$$b16
000180698 7001_ $$00000-0001-6753-3221$$aHuisman, Henkjan$$b17
000180698 7001_ $$aJarnagin, William R$$b18
000180698 7001_ $$aMcHugo, Maureen K$$b19
000180698 7001_ $$00000-0002-6876-5507$$aNapel, Sandy$$b20
000180698 7001_ $$00000-0002-1076-7948$$aPernicka, Jennifer S Golia$$b21
000180698 7001_ $$aRhode, Kawal$$b22
000180698 7001_ $$aTobon-Gomez, Catalina$$b23
000180698 7001_ $$aVorontsov, Eugene$$b24
000180698 7001_ $$aMeakin, James A$$b25
000180698 7001_ $$aOurselin, Sebastien$$b26
000180698 7001_ $$0P:(DE-He78)1042737c83ba70ec508bdd99f0096864$$aWiesenfarth, Manuel$$b27
000180698 7001_ $$aArbeláez, Pablo$$b28
000180698 7001_ $$00000-0003-2309-8517$$aBae, Byeonguk$$b29
000180698 7001_ $$aChen, Sihong$$b30
000180698 7001_ $$aDaza, Laura$$b31
000180698 7001_ $$00000-0002-5940-0063$$aFeng, Jianjiang$$b32
000180698 7001_ $$aHe, Baochun$$b33
000180698 7001_ $$0P:(DE-He78)7ea9af59d03ec7deb982a0e0562358fa$$aIsensee, Fabian$$b34
000180698 7001_ $$aJi, Yuanfeng$$b35
000180698 7001_ $$00000-0003-0075-979X$$aJia, Fucang$$b36
000180698 7001_ $$aKim, Ildoo$$b37
000180698 7001_ $$aMaier-Hein, Klaus$$b38
000180698 7001_ $$00000-0002-1672-2185$$aMerhof, Dorit$$b39
000180698 7001_ $$aPai, Akshay$$b40
000180698 7001_ $$aPark, Beomhee$$b41
000180698 7001_ $$00000-0002-0358-4692$$aPerslev, Mathias$$b42
000180698 7001_ $$aRezaiifar, Ramin$$b43
000180698 7001_ $$aRippel, Oliver$$b44
000180698 7001_ $$aSarasua, Ignacio$$b45
000180698 7001_ $$aShen, Wei$$b46
000180698 7001_ $$aSon, Jaemin$$b47
000180698 7001_ $$aWachinger, Christian$$b48
000180698 7001_ $$aWang, Liansheng$$b49
000180698 7001_ $$aWang, Yan$$b50
000180698 7001_ $$aXia, Yingda$$b51
000180698 7001_ $$aXu, Daguang$$b52
000180698 7001_ $$00000-0003-0225-7662$$aXu, Zhanwei$$b53
000180698 7001_ $$00000-0003-2195-2847$$aZheng, Yefeng$$b54
000180698 7001_ $$aSimpson, Amber L$$b55
000180698 7001_ $$0P:(DE-He78)26a1176cd8450660333a012075050072$$aMaier-Hein, Lena$$b56$$eLast author
000180698 7001_ $$00000-0003-1284-2558$$aCardoso, M Jorge$$b57
000180698 773__ $$0PERI:(DE-600)2553671-0$$a10.1038/s41467-022-30695-9$$gVol. 13, no. 1, p. 4128$$n1$$p4128$$tNature Communications$$v13$$x2041-1723$$y2022
000180698 909CO $$ooai:inrepo02.dkfz.de:180698$$pVDB
000180698 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)97e904f47dab556a77c0149cd0002591$$aDeutsches Krebsforschungszentrum$$b1$$kDKFZ
000180698 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)bb6a7a70f976eb8df1769944bf913596$$aDeutsches Krebsforschungszentrum$$b4$$kDKFZ
000180698 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)1042737c83ba70ec508bdd99f0096864$$aDeutsches Krebsforschungszentrum$$b27$$kDKFZ
000180698 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)7ea9af59d03ec7deb982a0e0562358fa$$aDeutsches Krebsforschungszentrum$$b34$$kDKFZ
000180698 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)26a1176cd8450660333a012075050072$$aDeutsches Krebsforschungszentrum$$b56$$kDKFZ
000180698 9131_ $$0G:(DE-HGF)POF4-315$$1G:(DE-HGF)POF4-310$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vBildgebung und Radioonkologie$$x0
000180698 9141_ $$y2022
000180698 915__ $$0LIC:(DE-HGF)CCBYNV$$2V:(DE-HGF)$$aCreative Commons Attribution CC BY (No Version)$$bDOAJ$$d2021-02-02
000180698 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2021-02-02
000180698 915__ $$0StatID:(DE-HGF)1190$$2StatID$$aDBCoverage$$bBiological Abstracts$$d2021-02-02
000180698 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2021-02-02
000180698 915__ $$0StatID:(DE-HGF)0561$$2StatID$$aArticle Processing Charges$$d2021-02-02
000180698 915__ $$0StatID:(DE-HGF)0700$$2StatID$$aFees$$d2021-02-02
000180698 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bNAT COMMUN : 2021$$d2022-11-11
000180698 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2022-11-11
000180698 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2022-11-11
000180698 915__ $$0StatID:(DE-HGF)0501$$2StatID$$aDBCoverage$$bDOAJ Seal$$d2021-10-13T14:44:21Z
000180698 915__ $$0StatID:(DE-HGF)0500$$2StatID$$aDBCoverage$$bDOAJ$$d2021-10-13T14:44:21Z
000180698 915__ $$0StatID:(DE-HGF)0030$$2StatID$$aPeer Review$$bDOAJ : Peer review$$d2021-10-13T14:44:21Z
000180698 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2022-11-11
000180698 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2022-11-11
000180698 915__ $$0StatID:(DE-HGF)1050$$2StatID$$aDBCoverage$$bBIOSIS Previews$$d2022-11-11
000180698 915__ $$0StatID:(DE-HGF)1030$$2StatID$$aDBCoverage$$bCurrent Contents - Life Sciences$$d2022-11-11
000180698 915__ $$0StatID:(DE-HGF)1040$$2StatID$$aDBCoverage$$bZoological Record$$d2022-11-11
000180698 915__ $$0StatID:(DE-HGF)1060$$2StatID$$aDBCoverage$$bCurrent Contents - Agriculture, Biology and Environmental Sciences$$d2022-11-11
000180698 915__ $$0StatID:(DE-HGF)1150$$2StatID$$aDBCoverage$$bCurrent Contents - Physical, Chemical and Earth Sciences$$d2022-11-11
000180698 915__ $$0StatID:(DE-HGF)9915$$2StatID$$aIF >= 15$$bNAT COMMUN : 2021$$d2022-11-11
000180698 9202_ $$0I:(DE-He78)E130-20160331$$kE130$$lE130 Intelligente Medizinische Systeme$$x0
000180698 9201_ $$0I:(DE-He78)E130-20160331$$kE130$$lE130 Intelligente Medizinische Systeme$$x0
000180698 9201_ $$0I:(DE-He78)C060-20160331$$kC060$$lC060 Biostatistik$$x1
000180698 9201_ $$0I:(DE-He78)E230-20160331$$kE230$$lE230 Medizinische Bildverarbeitung$$x2
000180698 980__ $$ajournal
000180698 980__ $$aVDB
000180698 980__ $$aI:(DE-He78)E130-20160331
000180698 980__ $$aI:(DE-He78)C060-20160331
000180698 980__ $$aI:(DE-He78)E230-20160331
000180698 980__ $$aUNRESTRICTED