Li, Hongwei BranHongwei BranLiConte, Gian MarcoGian MarcoConteAnwar, Syed MuhammadSyed MuhammadAnwarKofler, FlorianFlorianKoflerEzhov, IvanIvanEzhovvan Leemput, KoenKoenvan LeemputPiraud, MarieMariePiraudDiaz, MariaMariaDiazCole, ByroneByroneColeCalabrese, EvanEvanCalabreseRudie, JeffJeffRudieMeissen, FelixFelixMeissenAdewole, MarufMarufAdewoleJanas, AnastasiaAnastasiaJanasKazerooni, Anahita FathiAnahita FathiKazerooniLaBella, DominicDominicLaBellaMoawad, Ahmed WAhmed WMoawadFarahani, KeyvanKeyvanFarahaniEddy, JamesJamesEddyBergquist, TimothyTimothyBergquistChung, VerenaVerenaChungShinohara, Russell TakeshiRussell TakeshiShinoharaDako, FaroukFaroukDakoWiggins, WalterWalterWigginsReitman, ZacharyZacharyReitmanWang, ChunhaoChunhaoWangLiu, XinyangXinyangLiuJiang, ZhifanZhifanJiangFamiliar, ArianaArianaFamiliarJohanson, ElaineElaineJohansonMeier, ZekeZekeMeierDavatzikos, ChristosChristosDavatzikosFreymann, JohnJohnFreymannKirby, JustinJustinKirbyBilello, MichelMichelBilelloFathallah-Shaykh, Hassan MHassan MFathallah-ShaykhWiest, Roland Gerhard RudiRoland Gerhard RudiWiestKirschke, JanJanKirschkeColen, Rivka RRivka RColenKotrotsou, AikateriniAikateriniKotrotsouLamontagne, PamelaPamelaLamontagneMarcus, DanielDanielMarcusMilchenko, MikhailMikhailMilchenkoNazeri, ArashArashNazeriWeber, Marc-AndréMarc-AndréWeberMahajan, AbhishekAbhishekMahajanMohan, SuyashSuyashMohanMongan, JohnJohnMonganHess, ChristopherChristopherHessCha, SoonmeeSoonmeeChaVillanueva-Meyer, JavierJavierVillanueva-MeyerColak, ErrolErrolColakCrivellaro, PriscilaPriscilaCrivellaroJakab, AndrasAndrasJakabAlbrecht, JakeJakeAlbrechtAnazodo, UdunnaUdunnaAnazodoAboian, MariamMariamAboianYu, ThomasThomasYuChung, VerenaVerenaChungBergquist, TimothyTimothyBergquistEddy, JamesJamesEddyAlbrecht, JakeJakeAlbrechtBaid, UjjwalUjjwalBaidBakas, SpyridonSpyridonBakasLinguraru, Marius GeorgeMarius GeorgeLinguraruMenze, BjoernBjoernMenzeIglesias, Juan EugenioJuan EugenioIglesiasWiestler, BenediktBenediktWiestler2024-10-262024-10-262023-06-28https://boris-portal.unibe.ch/handle/20.500.12422/177054Automated brain tumor segmentation methods have become well-established and reached performance levels offering clear clinical utility. These methods typically rely on four input magnetic resonance imaging (MRI) modalities: T1-weighted images with and without contrast enhancement, T2-weighted images, and FLAIR images. However, some sequences are often missing in clinical practice due to time constraints or image artifacts, such as patient motion. Consequently, the ability to substitute missing modalities and gain segmentation performance is highly desirable and necessary for the broader adoption of these algorithms in the clinical routine. In this work, we present the establishment of the Brain MR Image Synthesis Benchmark (BraSyn) in conjunction with the Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2023. The primary objective of this challenge is to evaluate image synthesis methods that can realistically generate missing MRI modalities when multiple available images are provided. The ultimate aim is to facilitate automated brain tumor segmentation pipelines. The image dataset used in the benchmark is diverse and multi-modal, created through collaboration with various hospitals and research institutions.enBraTS MRI brain challenge image synthesis machine learning segmentation tumor600 - Technology::610 - Medicine & healthworking_paper10.48350/196332376089322305.09011v5