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A unified deep-learning network to accurately segment insulin granules of different animal models imaged under different electron microscopy methodologies
| Autores principales: | , , , , , , , , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Higher Education Press
2018
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6418072/ https://www.ncbi.nlm.nih.gov/pubmed/30306458 http://dx.doi.org/10.1007/s13238-018-0575-y |
| _version_ | 1783403656100446208 |
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| author | Zhang, Xiaoya Peng, Xiaohong Han, Chengsheng Zhu, Wenzhen Wei, Lisi Zhang, Yulin Wang, Yi Zhang, Xiuqin Tang, Hao Zhang, Jianshe Xu, Xiaojun Feng, Fengping Xue, Yanhong Yao, Erlin Tan, Guangming Xu, Tao Chen, Liangyi |
| author_facet | Zhang, Xiaoya Peng, Xiaohong Han, Chengsheng Zhu, Wenzhen Wei, Lisi Zhang, Yulin Wang, Yi Zhang, Xiuqin Tang, Hao Zhang, Jianshe Xu, Xiaojun Feng, Fengping Xue, Yanhong Yao, Erlin Tan, Guangming Xu, Tao Chen, Liangyi |
| author_sort | Zhang, Xiaoya |
| collection | PubMed |
| description | |
| format | Online Article Text |
| id | pubmed-6418072 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2018 |
| publisher | Higher Education Press |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-64180722019-04-03 A unified deep-learning network to accurately segment insulin granules of different animal models imaged under different electron microscopy methodologies Zhang, Xiaoya Peng, Xiaohong Han, Chengsheng Zhu, Wenzhen Wei, Lisi Zhang, Yulin Wang, Yi Zhang, Xiuqin Tang, Hao Zhang, Jianshe Xu, Xiaojun Feng, Fengping Xue, Yanhong Yao, Erlin Tan, Guangming Xu, Tao Chen, Liangyi Protein Cell Letter Higher Education Press 2018-10-10 2019-04 /pmc/articles/PMC6418072/ /pubmed/30306458 http://dx.doi.org/10.1007/s13238-018-0575-y Text en © The Author(s) 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
| spellingShingle | Letter Zhang, Xiaoya Peng, Xiaohong Han, Chengsheng Zhu, Wenzhen Wei, Lisi Zhang, Yulin Wang, Yi Zhang, Xiuqin Tang, Hao Zhang, Jianshe Xu, Xiaojun Feng, Fengping Xue, Yanhong Yao, Erlin Tan, Guangming Xu, Tao Chen, Liangyi A unified deep-learning network to accurately segment insulin granules of different animal models imaged under different electron microscopy methodologies |
| title | A unified deep-learning network to accurately segment insulin granules of different animal models imaged under different electron microscopy methodologies |
| title_full | A unified deep-learning network to accurately segment insulin granules of different animal models imaged under different electron microscopy methodologies |
| title_fullStr | A unified deep-learning network to accurately segment insulin granules of different animal models imaged under different electron microscopy methodologies |
| title_full_unstemmed | A unified deep-learning network to accurately segment insulin granules of different animal models imaged under different electron microscopy methodologies |
| title_short | A unified deep-learning network to accurately segment insulin granules of different animal models imaged under different electron microscopy methodologies |
| title_sort | unified deep-learning network to accurately segment insulin granules of different animal models imaged under different electron microscopy methodologies |
| topic | Letter |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6418072/ https://www.ncbi.nlm.nih.gov/pubmed/30306458 http://dx.doi.org/10.1007/s13238-018-0575-y |
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