The DOI matches its Crossref record.
Wide-field, high-resolution Fourier ptychographic microscopy
Open accessAbstract
We report an imaging method, termed Fourier ptychographic microscopy (FPM), which iteratively stitches together a number of variably illuminated, low-resolution intensity images in Fourier space to produce a wide-field, high-resolution complex sample image. By adopting a wavefront correction strategy, the FPM method can also correct for aberrations and digitally extend a microscope's depth of focus beyond the physical limitations of its optics.As a demonstration, we built a microscope prototype with a half-pitch resolution of 0.78 µm, a field of view of ∼120 mm2 and a resolution-invariant depth of focus of 0.3 mm (characterized at 632 nm). Gigapixel colour images of histology slides verify successful FPM operation. The reported imaging procedure transforms the general challenge of high-throughput, high-resolution microscopy from one that is coupled to the physical limitations of the system's optics to one that is solvable through computation. A wide-field, high-resolution imaging scheme that offers enhanced depth of field is demonstrated. The approach relies on stitching together time-multiplexed images in Fourier space.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Further improvements to the ptychographical iterative engine
Maiden, A., Johnson, D., & Li, P. (2017) · Optica · doi:10.1364/optica.4.000736 · Cited by 452
Single-shot quantitative phase gradient microscopy using a system of multifunctional metasurfaces
Kwon, H., Arbabi, E., Kamali, S. M., Faraji-Dana, M., & Faraon, A. (2020) · Nature Photonics · doi:10.1038/s41566-019-0536-x · Cited by 319
Reliable deep-learning-based phase imaging with uncertainty quantification
Xue, Y., Cheng, S., Li, Y., & Tian, L. (2019) · Optica · doi:10.1364/optica.6.000618 · Cited by 198
Metadata
- Authors
- Zheng, G., Horstmeyer, R., & Yang, C.
- Venue
- Nature Photonics
- Published
- 2013-07-28
- Volume
- 7
- Issue
- 9
- Pages
- 739-745
- ISSN
- 1749-4885 (ISSN-L)
- 1749-4893
- OpenAlex
- W2047602908
- Cited by
- 1,829
- References
- 0
- FWCI
- 71.03
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Wide-field, high-resolution Fourier ptychographic microscopy. https://app.cochat.ai/papers/10.1038/nphoton.2013.187
- The paper
- Zheng, G., Horstmeyer, R., & Yang, C. (2013). Wide-field, high-resolution Fourier ptychographic microscopy. Nature Photonics. https://doi.org/10.1038/nphoton.2013.187
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.