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Corrigendum: N-Net: A novel dense fully convolutional neural network for thyroid nodule segmentation
| Autores principales: | , , , , , , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Frontiers Media S.A.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9532001/ https://www.ncbi.nlm.nih.gov/pubmed/36203803 http://dx.doi.org/10.3389/fnins.2022.1034239 |
| _version_ | 1784802016671825920 |
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| author | Nie, Xingqing Zhou, Xiaogen Tong, Tong Lin, Xingtao Wang, Luoyan Zheng, Haonan Li, Jing Xue, Ensheng Chen, Shun Zheng, Meijuan Chen, Cong Du, Min |
| author_facet | Nie, Xingqing Zhou, Xiaogen Tong, Tong Lin, Xingtao Wang, Luoyan Zheng, Haonan Li, Jing Xue, Ensheng Chen, Shun Zheng, Meijuan Chen, Cong Du, Min |
| author_sort | Nie, Xingqing |
| collection | PubMed |
| description | |
| format | Online Article Text |
| id | pubmed-9532001 |
| institution | National Center for Biotechnology Information |
| language | English |
| publishDate | 2022 |
| publisher | Frontiers Media S.A. |
| record_format | MEDLINE/PubMed |
| spelling | pubmed-95320012022-10-05 Corrigendum: N-Net: A novel dense fully convolutional neural network for thyroid nodule segmentation Nie, Xingqing Zhou, Xiaogen Tong, Tong Lin, Xingtao Wang, Luoyan Zheng, Haonan Li, Jing Xue, Ensheng Chen, Shun Zheng, Meijuan Chen, Cong Du, Min Front Neurosci Neuroscience Frontiers Media S.A. 2022-09-20 /pmc/articles/PMC9532001/ /pubmed/36203803 http://dx.doi.org/10.3389/fnins.2022.1034239 Text en Copyright © 2022 Nie, Zhou, Tong, Lin, Wang, Zheng, Li, Xue, Chen, Zheng, Chen and Du. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
| spellingShingle | Neuroscience Nie, Xingqing Zhou, Xiaogen Tong, Tong Lin, Xingtao Wang, Luoyan Zheng, Haonan Li, Jing Xue, Ensheng Chen, Shun Zheng, Meijuan Chen, Cong Du, Min Corrigendum: N-Net: A novel dense fully convolutional neural network for thyroid nodule segmentation |
| title | Corrigendum: N-Net: A novel dense fully convolutional neural network for thyroid nodule segmentation |
| title_full | Corrigendum: N-Net: A novel dense fully convolutional neural network for thyroid nodule segmentation |
| title_fullStr | Corrigendum: N-Net: A novel dense fully convolutional neural network for thyroid nodule segmentation |
| title_full_unstemmed | Corrigendum: N-Net: A novel dense fully convolutional neural network for thyroid nodule segmentation |
| title_short | Corrigendum: N-Net: A novel dense fully convolutional neural network for thyroid nodule segmentation |
| title_sort | corrigendum: n-net: a novel dense fully convolutional neural network for thyroid nodule segmentation |
| topic | Neuroscience |
| url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9532001/ https://www.ncbi.nlm.nih.gov/pubmed/36203803 http://dx.doi.org/10.3389/fnins.2022.1034239 |
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