Whole-cell segmentation of tissue images with human-level performance using large-scale data annotation and deep learning

A principal challenge in the analysis of tissue imaging data is cell segmentation—the task of identifying the precise boundary of every cell in an image. To address this problem we constructed TissueNet, a dataset for training segmentation models that contains more than 1 million manually labeled ce...

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Veröffentlicht in:Nature biotechnology Jg. 40; H. 4; S. 555 - 565
Hauptverfasser: Greenwald, Noah F., Miller, Geneva, Moen, Erick, Kong, Alex, Kagel, Adam, Dougherty, Thomas, Fullaway, Christine Camacho, McIntosh, Brianna J., Leow, Ke Xuan, Schwartz, Morgan Sarah, Pavelchek, Cole, Cui, Sunny, Camplisson, Isabella, Bar-Tal, Omer, Singh, Jaiveer, Fong, Mara, Chaudhry, Gautam, Abraham, Zion, Moseley, Jackson, Warshawsky, Shiri, Soon, Erin, Greenbaum, Shirley, Risom, Tyler, Hollmann, Travis, Bendall, Sean C., Keren, Leeat, Graf, William, Angelo, Michael, Van Valen, David
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Nature Publishing Group US 01.04.2022
Nature Publishing Group
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ISSN:1087-0156, 1546-1696, 1546-1696
Online-Zugang:Volltext
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