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Field-dependent deep learning enables high-throughput whole-cell 3D super-resolution imaging.
Fu, Shuang; Shi, Wei; Luo, Tingdan; He, Yingchuan; Zhou, Lulu; Yang, Jie; Yang, Zhichao; Liu, Jiadong; Liu, Xiaotian; Guo, Zhiyong; Yang, Chengyu; Liu, Chao; Huang, Zhen-Li; Ries, Jonas; Zhang, Mingjie; Xi, Peng; Jin, Dayong; Li, Yiming.
Affiliation
  • Fu S; Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
  • Shi W; Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
  • Luo T; Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
  • He Y; Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
  • Zhou L; Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
  • Yang J; Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
  • Yang Z; Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
  • Liu J; School of Life Sciences, Southern University of Science and Technology, Shenzhen, China.
  • Liu X; School of Life Sciences, Southern University of Science and Technology, Shenzhen, China.
  • Guo Z; Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
  • Yang C; Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
  • Liu C; Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
  • Huang ZL; Key Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China.
  • Ries J; European Molecular Biology Laboratory, Cell Biology and Biophysics, Heidelberg, Germany.
  • Zhang M; School of Life Sciences, Southern University of Science and Technology, Shenzhen, China.
  • Xi P; Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
  • Jin D; Department of Biomedical Engineering, College of Future Technology, Peking University, Beijing, China.
  • Li Y; Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
Nat Methods ; 20(3): 459-468, 2023 03.
Article in En | MEDLINE | ID: mdl-36823335
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Deep Learning Language: En Journal: Nat Methods Journal subject: TECNICAS E PROCEDIMENTOS DE LABORATORIO Year: 2023 Type: Article Affiliation country: China
Fulltext
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Deep Learning Language: En Journal: Nat Methods Journal subject: TECNICAS E PROCEDIMENTOS DE LABORATORIO Year: 2023 Type: Article Affiliation country: China