001015298 001__ 1015298
001015298 005__ 20231122201849.0
001015298 0247_ $$2doi$$a10.48550/ARXIV.2308.05864
001015298 0247_ $$2doi$$a10.48550/arXiv.2308.05864
001015298 0247_ $$2datacite_doi$$a10.34734/FZJ-2023-03643
001015298 037__ $$aFZJ-2023-03643
001015298 041__ $$aEnglish
001015298 1001_ $$aMa, Jun$$b0
001015298 245__ $$aThe Multi-modality Cell Segmentation Challenge: Towards Universal Solutions
001015298 260__ $$barXiv$$c2023
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001015298 3367_ $$2BibTeX$$aARTICLE
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001015298 520__ $$aCell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyperparameters in different experimental settings. Here, we present a multi-modality cell segmentation benchmark, comprising over 1500 labeled images derived from more than 50 diverse biological experiments. The top participants developed a Transformer-based deep-learning algorithm that not only exceeds existing methods, but can also be applied to diverse microscopy images across imaging platforms and tissue types without manual parameter adjustments. This benchmark and the improved algorithm offer promising avenues for more accurate and versatile cell analysis in microscopy imaging.
001015298 536__ $$0G:(DE-HGF)POF4-5254$$a5254 - Neuroscientific Data Analytics and AI (POF4-525)$$cPOF4-525$$fPOF IV$$x0
001015298 536__ $$0G:(GEPRIS)347572269$$aDFG project 347572269 - Heterogenität von Zytoarchitektur, Chemoarchitektur und Konnektivität in einem großskaligen Computermodell der menschlichen Großhirnrinde (347572269)$$c347572269$$x1
001015298 536__ $$0G:(EU-Grant)945539$$aHBP SGA3 - Human Brain Project Specific Grant Agreement 3 (945539)$$c945539$$fH2020-SGA-FETFLAG-HBP-2019$$x2
001015298 536__ $$0G:(DE-HGF)InterLabs-0015$$aHIBALL - Helmholtz International BigBrain Analytics and Learning Laboratory (HIBALL) (InterLabs-0015)$$cInterLabs-0015$$x3
001015298 536__ $$0G:(DE-Juel-1)E.40401.62$$aHelmholtz AI - Helmholtz Artificial Intelligence  Coordination Unit – Local Unit FZJ (E.40401.62)$$cE.40401.62$$x4
001015298 588__ $$aDataset connected to DataCite
001015298 650_7 $$2Other$$aImage and Video Processing (eess.IV)
001015298 650_7 $$2Other$$aComputer Vision and Pattern Recognition (cs.CV)
001015298 650_7 $$2Other$$aMachine Learning (cs.LG)
001015298 650_7 $$2Other$$aQuantitative Methods (q-bio.QM)
001015298 650_7 $$2Other$$aFOS: Electrical engineering, electronic engineering, information engineering
001015298 650_7 $$2Other$$aFOS: Computer and information sciences
001015298 650_7 $$2Other$$aFOS: Biological sciences
001015298 7001_ $$aXie, Ronald$$b1
001015298 7001_ $$aAyyadhury, Shamini$$b2
001015298 7001_ $$aGe, Cheng$$b3
001015298 7001_ $$aGupta, Anubha$$b4
001015298 7001_ $$aGupta, Ritu$$b5
001015298 7001_ $$aGu, Song$$b6
001015298 7001_ $$aZhang, Yao$$b7
001015298 7001_ $$aLee, Gihun$$b8
001015298 7001_ $$aKim, Joonkee$$b9
001015298 7001_ $$aLou, Wei$$b10
001015298 7001_ $$aLi, Haofeng$$b11
001015298 7001_ $$0P:(DE-Juel1)177675$$aUpschulte, Eric$$b12$$ufzj
001015298 7001_ $$0P:(DE-Juel1)165746$$aDickscheid, Timo$$b13$$ufzj
001015298 7001_ $$ade Almeida, José Guilherme$$b14
001015298 7001_ $$aWang, Yixin$$b15
001015298 7001_ $$aHan, Lin$$b16
001015298 7001_ $$aYang, Xin$$b17
001015298 7001_ $$aLabagnara, Marco$$b18
001015298 7001_ $$aRahi, Sahand Jamal$$b19
001015298 7001_ $$aKempster, Carly$$b20
001015298 7001_ $$aPollitt, Alice$$b21
001015298 7001_ $$aEspinosa, Leon$$b22
001015298 7001_ $$aMignot, Tâm$$b23
001015298 7001_ $$aMiddeke, Jan Moritz$$b24
001015298 7001_ $$aEckardt, Jan-Niklas$$b25
001015298 7001_ $$aLi, Wangkai$$b26
001015298 7001_ $$aLi, Zhaoyang$$b27
001015298 7001_ $$aCai, Xiaochen$$b28
001015298 7001_ $$aBai, Bizhe$$b29
001015298 7001_ $$aGreenwald, Noah F.$$b30
001015298 7001_ $$aVan Valen, David$$b31
001015298 7001_ $$aWeisbart, Erin$$b32
001015298 7001_ $$aCimini, Beth A.$$b33
001015298 7001_ $$aLi, Zhuoshi$$b34
001015298 7001_ $$aZuo, Chao$$b35
001015298 7001_ $$aBrück, Oscar$$b36
001015298 7001_ $$aBader, Gary D.$$b37
001015298 7001_ $$0P:(DE-HGF)0$$aWang, Bo$$b38$$eCorresponding author
001015298 773__ $$a10.48550/arXiv.2308.05864$$tarxiv$$y2023
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001015298 9141_ $$y2023
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