Evidence map›Paper›PMID 36823335›Full record

ArticleNature methods2023

Field-dependent deep learning enables high-throughput whole-cell 3D super-resolution imaging.

Shuang Fu, Wei Shi, Tingdan Luo, Yingchuan He, Lulu Zhou, Jie Yang, Zhichao Yang, Jiadong Liu, Xiaotian Liu, Zhiyong Guo and 8 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

46 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Deep Learning for Localization Microscopy in 2D and 3D.Accounts of chemical research · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Case Study: Illuminating the Nanoscale World of Microbiology.Methods in molecular biology (Clifton, N.J.) · 2026
    Review
  11. Article
  12. Article
  13. Review
  14. Article
  15. Article
  16. Cryosectioning-enhanced super-resolution microscopy for single-protein imaging across cells and tissues.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  17. Article
  18. Taking a closer look at matrix vesicle biogenesis.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2025
    Review
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Shuang Fu *Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.ORCID http://orcid.org/0000-0003-0132-5707
Wei Shi *Guangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
Tingdan LuoGuangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
Yingchuan HeGuangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
Lulu ZhouGuangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
Jie YangGuangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.ORCID http://orcid.org/0000-0001-8172-0736
Zhichao YangGuangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
Jiadong LiuSchool of Life Sciences, Southern University of Science and Technology, Shenzhen, China.
Xiaotian LiuSchool of Life Sciences, Southern University of Science and Technology, Shenzhen, China.ORCID http://orcid.org/0000-0001-5009-1287
Zhiyong GuoGuangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
Chengyu YangGuangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
Chao LiuGuangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
Zhen-Li HuangKey Laboratory of Biomedical Engineering of Hainan Province, School of Biomedical Engineering, Hainan University, Haikou, China.ORCID http://orcid.org/0000-0003-2400-966X
Jonas RiesEuropean Molecular Biology Laboratory, Cell Biology and Biophysics, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-6640-9250
Mingjie ZhangSchool of Life Sciences, Southern University of Science and Technology, Shenzhen, China.
Peng XiGuangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.
Dayong JinGuangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China.ORCID http://orcid.org/0000-0003-1046-2666
Yiming LiGuangdong Provincial Key Laboratory of Advanced Biomaterials, Department of Biomedical Engineering, Southern University of Science and Technology, Shenzhen, China. liym2019@sustech.edu.cn.ORCID http://orcid.org/0000-0003-4109-3824

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Single-molecule localization microscopy in a typical wide-field setup has been widely used for investigating subcellular structures with super resolution; however, field-dependent aberrations restrict the field of view (FOV) to only tens of micrometers. Here, we present a deep-learning method for precise localization of spatially variant point emitters (FD-DeepLoc) over a large FOV covering the full chip of a modern sCMOS camera. Using a graphic processing unit-based vectorial point spread function (PSF) fitter, we can fast and accurately model the spatially variant PSF of a high numerical aperture objective in the entire FOV. Combined with deformable mirror-based optimal PSF engineering, we demonstrate high-accuracy three-dimensional single-molecule localization microscopy over a volume of ~180 × 180 × 5 μm

Indexed as

Deep LearningImaging, Three-DimensionalSingle Molecule Imaging

Identifiers

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.