UnMICST: Deep learning with real augmentation for robust segmentation of highly multiplexed images of human tissues
Presenting UnMICST, strategies for robust single-cell segmentation in challenging human tissues.
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2022-11-01
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| Series: | Communications Biology |
| Online Access: | https://doi.org/10.1038/s42003-022-04076-3 |
| _version_ | 1797984100185800704 |
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| author | Clarence Yapp Edward Novikov Won-Dong Jang Tuulia Vallius Yu-An Chen Marcelo Cicconet Zoltan Maliga Connor A. Jacobson Donglai Wei Sandro Santagata Hanspeter Pfister Peter K. Sorger |
| author_facet | Clarence Yapp Edward Novikov Won-Dong Jang Tuulia Vallius Yu-An Chen Marcelo Cicconet Zoltan Maliga Connor A. Jacobson Donglai Wei Sandro Santagata Hanspeter Pfister Peter K. Sorger |
| author_sort | Clarence Yapp |
| collection | DOAJ |
| description | Presenting UnMICST, strategies for robust single-cell segmentation in challenging human tissues. |
| first_indexed | 2024-04-11T06:57:14Z |
| format | Article |
| id | doaj.art-d6d934461012487bae14696dab27c9da |
| institution | Directory Open Access Journal |
| issn | 2399-3642 |
| language | English |
| last_indexed | 2024-04-11T06:57:14Z |
| publishDate | 2022-11-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Biology |
| spelling | doaj.art-d6d934461012487bae14696dab27c9da2022-12-22T04:39:01ZengNature PortfolioCommunications Biology2399-36422022-11-015111310.1038/s42003-022-04076-3UnMICST: Deep learning with real augmentation for robust segmentation of highly multiplexed images of human tissuesClarence Yapp0Edward Novikov1Won-Dong Jang2Tuulia Vallius3Yu-An Chen4Marcelo Cicconet5Zoltan Maliga6Connor A. Jacobson7Donglai Wei8Sandro Santagata9Hanspeter Pfister10Peter K. Sorger11Laboratory of Systems Pharmacology, Harvard Medical SchoolLaboratory of Systems Pharmacology, Harvard Medical SchoolLaboratory of Systems Pharmacology, Harvard Medical SchoolLaboratory of Systems Pharmacology, Harvard Medical SchoolLaboratory of Systems Pharmacology, Harvard Medical SchoolImage and Data Analysis Core, Harvard Medical SchoolLaboratory of Systems Pharmacology, Harvard Medical SchoolLaboratory of Systems Pharmacology, Harvard Medical SchoolSchool of Engineering and Applied Sciences, Harvard UniversityLaboratory of Systems Pharmacology, Harvard Medical SchoolSchool of Engineering and Applied Sciences, Harvard UniversityLaboratory of Systems Pharmacology, Harvard Medical SchoolPresenting UnMICST, strategies for robust single-cell segmentation in challenging human tissues.https://doi.org/10.1038/s42003-022-04076-3 |
| spellingShingle | Clarence Yapp Edward Novikov Won-Dong Jang Tuulia Vallius Yu-An Chen Marcelo Cicconet Zoltan Maliga Connor A. Jacobson Donglai Wei Sandro Santagata Hanspeter Pfister Peter K. Sorger UnMICST: Deep learning with real augmentation for robust segmentation of highly multiplexed images of human tissues Communications Biology |
| title | UnMICST: Deep learning with real augmentation for robust segmentation of highly multiplexed images of human tissues |
| title_full | UnMICST: Deep learning with real augmentation for robust segmentation of highly multiplexed images of human tissues |
| title_fullStr | UnMICST: Deep learning with real augmentation for robust segmentation of highly multiplexed images of human tissues |
| title_full_unstemmed | UnMICST: Deep learning with real augmentation for robust segmentation of highly multiplexed images of human tissues |
| title_short | UnMICST: Deep learning with real augmentation for robust segmentation of highly multiplexed images of human tissues |
| title_sort | unmicst deep learning with real augmentation for robust segmentation of highly multiplexed images of human tissues |
| url | https://doi.org/10.1038/s42003-022-04076-3 |
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