Novel segmentation strategies for fully-automated analysis of yeast images
O'Brien, Jennifer and Hoque, Sanaul and Mulvihill, Daniel P. and Sirlantzis, Konstantinos (2017) Novel segmentation strategies for fully-automated analysis of yeast images. [Data Collection]
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Image data and ground truths associated with O'Brien et al.
| Uncontrolled keywords: | pombe, automated segmentation, image datasets, image groundtruths | ||
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| Subjects: | Q Science > QH Natural history > QH301 Biology T Technology > T Technology (General) |
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| DOI: | 10.22024/UniKent/01.01/24 | ||
| Institutional Unit: | Schools > School of Natural Sciences > Biosciences Schools > School of Computing |
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| Former Institutional Unit: |
Divisions > Division of Natural Sciences > School of Computing Divisions > Division of Natural Sciences > Biosciences Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
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| Depositing User: | Daniel Mulvihill | ||
| Collection period: | From To 2014 2017 |
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| Last Modified: | 03 Jun 2025 08:37 | ||
| Publication Date: | 24 November 2017 | ||
| URI: | https://data.kent.ac.uk/id/eprint/24 | ||
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https://orcid.org/0000-0001-8627-3429
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