Fourier Ptychographic Neural Network Combined with Zernike Aberration Recovery and Wirtinger Flow Optimization.

Xiaoli Wang, Zechuan Lin, Yan Wang, Jie Li, Xinbo Wang, Hao Wang

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

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0citing 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

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Xiaoli WangElectronics Information Engineering College, Changchun University, Changchun 130022, China.

Zechuan LinElectronics Information Engineering College, Changchun University, Changchun 130022, China.

Yan WangElectronics Information Engineering College, Changchun University, Changchun 130022, China.

Jie LiElectronics Information Engineering College, Changchun University, Changchun 130022, China.

Xinbo WangElectronics Information Engineering College, Changchun University, Changchun 130022, China.

Hao WangElectronics Information Engineering College, Changchun University, Changchun 130022, China.

Funding

the Jilin Provincial Science and Technology Department 2021JBH02L38the Science and Technology Development Plan Projects of Jilin Province YDZJ202301ZYTS180

6 · The paper itself

Abstract

Fourier ptychographic microscopy, as a computational imaging method, can reconstruct high-resolution images but suffers optical aberration, which affects its imaging quality. For this reason, this paper proposes a network model for simulating the forward imaging process in the Tensorflow framework using samples and coherent transfer functions as the input. The proposed model improves the introduced Wirtinger flow algorithm, retains the central idea, simplifies the calculation process, and optimizes the update through back propagation. In addition, Zernike polynomials are used to accurately estimate aberration. The simulation and experimental results show that this method can effectively improve the accuracy of aberration correction, maintain good correction performance under complex scenes, and reduce the influence of optical aberration on imaging quality.

Indexed as

aberration correctionFourier ptychographic microscopypupil recoveryWirtinger FlowZernike polynomials

Identifiers

PMID38474984

DOI10.3390/s24051448

PMCPMC10935293

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

Registered trials

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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.