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Journal articles on the topic 'Fourier Ptychographic Microscopy'

Author: Grafiati

Published: 7 September 2024

Last updated: 31 July 2025

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1

Jizhou Zhang, Jizhou Zhang, Tingfa Xu Tingfa Xu, Xing Wang Xing Wang, Sining Chen Sining Chen, and Guoqiang Ni Guoqiang Ni. "Fast gradational reconstruction for Fourier ptychographic microscopy." Chinese Optics Letters 15, no. 11 (2017): 111702. http://dx.doi.org/10.3788/col201715.111702.

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2

Ou, Xiaoze, Jaebum Chung, Roarke Horstmeyer, and Changhuei Yang. "Aperture scanning Fourier ptychographic microscopy." Biomedical Optics Express 7, no. 8 (2016): 3140. http://dx.doi.org/10.1364/boe.7.003140.

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3

Wang, Lin, Qihao Song, Hongbo Zhang, Caojin Yuan, and Ting-Chung Poon. "Optical scanning Fourier ptychographic microscopy." Applied Optics 60, no. 4 (2020): A243. http://dx.doi.org/10.1364/ao.402644.

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4

Loetgering, Lars, Tomas Aidukas, Kevin C. Zhou, Felix Wechsler, and Roarke Horstmeyer. "Fourier Ptychography Part II: Phase Retrieval and High-Resolution Image Formation." Microscopy Today 30, no. 5 (2022): 36–39. http://dx.doi.org/10.1017/s1551929522001055.

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Abstract:This article is the second within a three-part series on Fourier ptychography, which is a computational microscopy technique for high-resolution, large field-of-view imaging. While the first article laid out the basics of Fourier ptychography, this second part sheds light on its algorithmic ingredients. We present a non-technical discussion of phase retrieval, which allows for the synthesis of high-resolution images from a sequence of low-resolution raw data. Fourier ptychographic phase retrieval can be carried out on standard, widefield microscopy platforms with the simple addition o

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5

Zhang, Yongbing, Weixin Jiang, Lei Tian, Laura Waller, and Qionghai Dai. "Self-learning based Fourier ptychographic microscopy." Optics Express 23, no. 14 (2015): 18471. http://dx.doi.org/10.1364/oe.23.018471.

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6

Liu, Qiulan, Yue Fang, Renjie Zhou, Peng Xiu, Cuifang Kuang, and Xu Liu. "Surface wave illumination Fourier ptychographic microscopy." Optics Letters 41, no. 22 (2016): 5373. http://dx.doi.org/10.1364/ol.41.005373.

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7

Zhou, You, Jiamin Wu, Zichao Bian, Jinli Suo, Guoan Zheng, and Qionghai Dai. "Fourier ptychographic microscopy using wavelength multiplexing." Journal of Biomedical Optics 22, no. 6 (2017): 066006. http://dx.doi.org/10.1117/1.jbo.22.6.066006.

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8

Horstmeyer, Roarke, Guoan Zheng, Xiaoze Ou, and Changhuei Yang. "Modeling Extensions of Fourier Ptychographic Microscopy." Microscopy and Microanalysis 20, S3 (2014): 370–71. http://dx.doi.org/10.1017/s1431927614003572.

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9

Xiu, Peng, Youhua Chen, Cuifang Kuang, et al. "Structured illumination fluorescence Fourier ptychographic microscopy." Optics Communications 381 (December 2016): 100–106. http://dx.doi.org/10.1016/j.optcom.2016.06.075.

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10

Huang, Kaicheng, Wangwei Hui, Qing Ye, et al. "Compressed-sampling-based Fourier ptychographic microscopy." Optics Communications 452 (December 2019): 18–24. http://dx.doi.org/10.1016/j.optcom.2019.07.009.

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11

Pan, An, Chao Zuo, Yuege Xie, Ming Lei, and Baoli Yao. "Vignetting effect in Fourier ptychographic microscopy." Optics and Lasers in Engineering 120 (September 2019): 40–48. http://dx.doi.org/10.1016/j.optlaseng.2019.02.015.

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12

Zhang, Peiwei, Jufeng Zhao, Binbin Lin, Xiaohui Wu, and Guangmang Cui. "Hyperspectral microscopy imaging based on Fourier ptychographic microscopy." Journal of Optics 24, no. 5 (2022): 055301. http://dx.doi.org/10.1088/2040-8986/ac57b3.

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Abstract Hyperspectral resolution, high spatial resolution, and a wide field of view (FOV) are the targets of optical spectral microscopy imaging. However, hyperspectral microscopy imaging technology cannot provide a wide FOV and a high spatial resolution at the same time. Fourier ptychographic microscopy (FPM) is a novel microscopy imaging technique that uses LEDs at varying angles to capture a series of low-spatial-resolution images that are used to recover images that have both high spatial resolution and a wide FOV. Since FPM cannot obtain the spectral resolution of the sample, in this pap

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13

Zhang Jinhua, 张瑾华, 张继洲 Zhang Jizhou, 李佳男 Li Jianan та ін. "基于叠层衍射成像的傅里叶叠层显微像差校正方法". Acta Optica Sinica 41, № 10 (2021): 1011001. http://dx.doi.org/10.3788/aos202141.1011001.

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14

Fouché, E. E., G. W. Bosman, and P. H. Neethling. "Polarization-sensitive Fourier ptychographic microscopy for high-resolution, large area birefringence imaging of petrographic thin sections." Journal of Physics: Conference Series 2970, no. 1 (2025): 012007. https://doi.org/10.1088/1742-6596/2970/1/012007.

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Abstract Polarization-sensitive Fourier ptychographic microscopy (ps-FPM) combines polarized light microscopy with Fourier ptychographic microscopy to image birefringent samples in high-resolution over a large field of view. Measurement of the anisotropy properties allows the samples to be viewed with greater contrast and to distinguish between sample regions that would otherwise be indistinguishable. In this work, ps-FPM is used to image birefringent petrographic thin sections to view the different crystal domains and to distinguish between the different minerals in the rock sample, a require

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15

Carlsen, Mads, Trygve M. Ræder, Can Yildirim, Raquel Rodriguez-Lamas, Carsten Detlefs, and Hugh Simons. "Fourier ptychographic dark field x-ray microscopy." Optics Express 30, no. 2 (2022): 2949. http://dx.doi.org/10.1364/oe.447657.

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16

Sun Jiasong, 孙佳嵩, 张玉珍 Zhang Yuzhen, 陈钱 Chen Qian, and 左超 Zuo Chao. "Fourier Ptychographic Microscopy: Theory, Advances, and Applications." Acta Optica Sinica 36, no. 10 (2016): 1011005. http://dx.doi.org/10.3788/aos201636.1011005.

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17

Ou, Xiaoze, Roarke Horstmeyer, Changhuei Yang, and Guoan Zheng. "Quantitative phase imaging via Fourier ptychographic microscopy." Optics Letters 38, no. 22 (2013): 4845. http://dx.doi.org/10.1364/ol.38.004845.

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18

Zhang, Yongbing, Weixin Jiang, and Qionghai Dai. "Nonlinear optimization approach for Fourier ptychographic microscopy." Optics Express 23, no. 26 (2015): 33822. http://dx.doi.org/10.1364/oe.23.033822.

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19

Zhu, Youqiang, Minglu Sun, Xiong Chen, et al. "Single full-FOV reconstruction Fourier ptychographic microscopy." Biomedical Optics Express 11, no. 12 (2020): 7175. http://dx.doi.org/10.1364/boe.409952.

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20

Yang Jiaqi, 杨佳琪, 马. 骁. Ma Xiao, 林锦新 Lin Jinxin, and 钟金钢 Zhong Jingang. "Intensity Correction Research for Fourier Ptychographic Microscopy." Laser & Optoelectronics Progress 54, no. 3 (2017): 031101. http://dx.doi.org/10.3788/lop54.031101.

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21

Pan, An, Yan Zhang, Tianyu Zhao, et al. "System calibration method for Fourier ptychographic microscopy." Journal of Biomedical Optics 22, no. 09 (2017): 1. http://dx.doi.org/10.1117/1.jbo.22.9.096005.

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22

Fan, Yao, Jiasong Sun, Qian Chen, Mingqun Wang, and Chao Zuo. "Adaptive denoising method for Fourier ptychographic microscopy." Optics Communications 404 (December 2017): 23–31. http://dx.doi.org/10.1016/j.optcom.2017.05.026.

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23

Zheng, Guoan, Roarke Horstmeyer, and Changhuei Yang. "Wide-field, high-resolution Fourier ptychographic microscopy." Nature Photonics 7, no. 9 (2013): 739–45. http://dx.doi.org/10.1038/nphoton.2013.187.

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24

Wang, Xiaoli, Yan Piao, Yuanshang Jin, et al. "Fourier Ptychographic Reconstruction Method of Self-Training Physical Model." Applied Sciences 13, no. 6 (2023): 3590. http://dx.doi.org/10.3390/app13063590.

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Fourier ptychographic microscopy is a new microscopic computational imaging technology. A series of low-resolution intensity images are collected by a Fourier ptychographic microscopy system, and high-resolution intensity and phase images are reconstructed from the collected low-resolution images by a reconstruction algorithm. It is a kind of microscopy that can achieve both a large field of view and high resolution. Here in this article, a Fourier ptychographic reconstruction method applied to a self-training physical model is proposed. The SwinIR network in the field of super-resolution is i

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25

Chen Yican, 陈奕灿, 吴霞 Wu Xia, 罗志 Luo Zhi, 杨恢东 Yang Huidong, and 黄波 Huang Bo. "Fourier Ptychographic Microscopy Reconstruction Based on Deep Learning." Laser & Optoelectronics Progress 57, no. 22 (2020): 221106. http://dx.doi.org/10.3788/lop57.221106.

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26

Zheng, Guoan, Xiaoze Ou, Roarke Horstmeyer, Jaebum Chung, and Changhuei Yang. "Fourier Ptychographic Microscopy: A Gigapixel Superscope for Biomedicine." Optics and Photonics News 25, no. 4 (2014): 26. http://dx.doi.org/10.1364/opn.25.4.000026.

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27

Zhang, Yan, An Pan, and Ming Lei. "Data preprocessing methods for robust Fourier ptychographic microscopy." Optical Engineering 56, no. 12 (2017): 1. http://dx.doi.org/10.1117/1.oe.56.12.123107.

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28

Lee, Hwihyeong, Byong Hyuk Chon, and Hee Kyung Ahn. "Reflective Fourier ptychographic microscopy using a parabolic mirror." Optics Express 27, no. 23 (2019): 34382. http://dx.doi.org/10.1364/oe.27.034382.

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29

Ou, Xiaoze, Guoan Zheng, and Changhuei Yang. "Embedded pupil function recovery for Fourier ptychographic microscopy." Optics Express 22, no. 5 (2014): 4960. http://dx.doi.org/10.1364/oe.22.004960.

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30

Hou, Lexin, Hexin Wang, Markus Sticker, Lars Stoppe, Junhua Wang, and Min Xu. "Adaptive background interference removal for Fourier ptychographic microscopy." Applied Optics 57, no. 7 (2018): 1575. http://dx.doi.org/10.1364/ao.57.001575.

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31

Horstmeyer, Roarke, and Changhuei Yang. "A phase space model of Fourier ptychographic microscopy." Optics Express 22, no. 1 (2014): 338. http://dx.doi.org/10.1364/oe.22.000338.

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32

Konda, Pavan Chandra, Jonathan M. Taylor, and Andrew R. Harvey. "Multi-aperture Fourier ptychographic microscopy, theory and validation." Optics and Lasers in Engineering 138 (March 2021): 106410. http://dx.doi.org/10.1016/j.optlaseng.2020.106410.

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33

Lee, Byounghyo, Jong-young Hong, Dongheon Yoo, et al. "Single-shot phase retrieval via Fourier ptychographic microscopy." Optica 5, no. 8 (2018): 976. http://dx.doi.org/10.1364/optica.5.000976.

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34

Zhang, Jizhou, Tingfa Xu, Jingdan Liu, Sining Chen, and Xing Wang. "Precise Brightfield Localization Alignment for Fourier Ptychographic Microscopy." IEEE Photonics Journal 10, no. 1 (2018): 1–13. http://dx.doi.org/10.1109/jphot.2017.2780189.

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35

Ni, Ying-Hui, Si-Yuan Fan, Shu-Yuan Zhang, and Ming-Jie Sun. "Hyperuniform illumination subsampling method for Fourier ptychographic microscopy." Optics and Lasers in Engineering 176 (May 2024): 108106. http://dx.doi.org/10.1016/j.optlaseng.2024.108106.

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36

Xu, Fannuo, Zipei Wu, Chao Tan, et al. "Fourier Ptychographic Microscopy 10 Years on: A Review." Cells 13, no. 4 (2024): 324. http://dx.doi.org/10.3390/cells13040324.

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Fourier ptychographic microscopy (FPM) emerged as a prominent imaging technique in 2013, attracting significant interest due to its remarkable features such as precise phase retrieval, expansive field of view (FOV), and superior resolution. Over the past decade, FPM has become an essential tool in microscopy, with applications in metrology, scientific research, biomedicine, and inspection. This achievement arises from its ability to effectively address the persistent challenge of achieving a trade-off between FOV and resolution in imaging systems. It has a wide range of applications, including

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37

Chen, Jiurun, Fengze Sui, Muyao Chen, et al. "Deep learning-based fast multispectral Fourier ptychographic microscopy." Optics & Laser Technology 192 (December 2025): 113464. https://doi.org/10.1016/j.optlastec.2025.113464.

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38

Wang, Xiaoli, Yan Piao, Jie Li, and Jinyang Yu. "Fourier Ptychographic Microscopy Reconstruction Method Based on Residual Transfer Networks." Journal of Physics: Conference Series 2400, no. 1 (2022): 012015. http://dx.doi.org/10.1088/1742-6596/2400/1/012015.

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Abstract Fourier ptychographic microscopy reconstruction mostly adopts the traditional alternating iterative phase recovery method and optimization method, which has high computational complexity, high redundancy of image acquisition data, low reconstruction quality and high time consumption. In this paper, the model of residual transfer networks based on Resnet152 is proposed for Fourier ptychographic microscopy reconstruction, the learning process of deep convolution neural network is introduced, and the image reconstruction method based on deep learning realizes the end-to-end reconstructio

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39

Zheng, Chuanjian, Tianyu Wang, Zhan Li, et al. "Quantitative phase imaging based on Fourier ptychographic microscopy: advances, applications, and perspectives." Advanced Imaging 2, no. 3 (2025): 032001. https://doi.org/10.3788/ai.2025.20001.

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40

Wang, Yan, Shuo Wan, Yongshan Wang, Jie Li, and Nan Guan. "Color fourier ptychographic microscopy reconstruction based on double contrast learning." Physica Scripta 100, no. 4 (2025): 046009. https://doi.org/10.1088/1402-4896/adbe04.

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Abstract Fourier ptychographic microscopy (FPM), as an advanced digital imaging technique, holds significant potential in the pathology field. Color FPM images are essential for accurate pathological analysis. Currently, color FPM images are primarily acquired through modifications in imaging devices or virtual staining algorithms. However, the complexity of pathological slides often results in unclear image details during the imaging process, thereby impacting the subsequent colorization outcomes. To address these challenges, we propose an enhanced dual-contrast learning virtual staining algo

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41

Alotaibi, Maged F. "Reconstruction of Talbot self-image using Fourier ptychographic microscopy." Alexandria Engineering Journal 61, no. 12 (2022): 12151–57. http://dx.doi.org/10.1016/j.aej.2022.06.016.

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42

Wang, Aiye, Zhuoqun Zhang, Siqi Wang, An Pan, Caiwen Ma, and Baoli Yao. "Fourier Ptychographic Microscopy via Alternating Direction Method of Multipliers." Cells 11, no. 9 (2022): 1512. http://dx.doi.org/10.3390/cells11091512.

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Fourier ptychographic microscopy (FPM) has risen as a promising computational imaging technique that breaks the trade-off between high resolution and large field of view (FOV). Its reconstruction is normally formulated as a blind phase retrieval problem, where both the object and probe have to be recovered from phaseless measured data. However, the stability and reconstruction quality may dramatically deteriorate in the presence of noise interference. Herein, we utilized the concept of alternating direction method of multipliers (ADMM) to solve this problem (termed ADMM-FPM) by breaking it int

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43

Tao, Xiao, Jinlei Zhang, Peng Sun, et al. "Phase-coded speckle illumination for laser Fourier ptychographic microscopy." Optics Communications 498 (November 2021): 127199. http://dx.doi.org/10.1016/j.optcom.2021.127199.

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44

Kuang, Cuifang, Ye Ma, Renjie Zhou, et al. "Digital micromirror device-based laser-illumination Fourier ptychographic microscopy." Optics Express 23, no. 21 (2015): 26999. http://dx.doi.org/10.1364/oe.23.026999.

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45

Ou, Xiaoze, Guoan Zheng, and Changhuei Yang. "Embedded pupil function recovery for Fourier ptychographic microscopy: erratum." Optics Express 23, no. 26 (2015): 33027. http://dx.doi.org/10.1364/oe.23.033027.

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46

Zheng, Guoan, Roarke Horstmeyer, and Changhuei Yang. "Erratum: Corrigendum: Wide-field, high-resolution Fourier ptychographic microscopy." Nature Photonics 9, no. 9 (2015): 621. http://dx.doi.org/10.1038/nphoton.2015.148.

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47

Sun, Jiasong, Qian Chen, Yuzhen Zhang, and Chao Zuo. "Efficient positional misalignment correction method for Fourier ptychographic microscopy." Biomedical Optics Express 7, no. 4 (2016): 1336. http://dx.doi.org/10.1364/boe.7.001336.

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48

Chung, Jaebum, Hangwen Lu, Xiaoze Ou, Haojiang Zhou, and Changhuei Yang. "Wide-field Fourier ptychographic microscopy using laser illumination source." Biomedical Optics Express 7, no. 11 (2016): 4787. http://dx.doi.org/10.1364/boe.7.004787.

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49

Zhang, Jizhou, Tingfa Xu, Ziyi Shen, Yifan Qiao, and Yizhou Zhang. "Fourier ptychographic microscopy reconstruction with multiscale deep residual network." Optics Express 27, no. 6 (2019): 8612. http://dx.doi.org/10.1364/oe.27.008612.

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50

Zhang, Jizhou, Tingfa Xu, Sining Chen, and Xing Wang. "Efficient Colorful Fourier Ptychographic Microscopy Reconstruction With Wavelet Fusion." IEEE Access 6 (2018): 31729–39. http://dx.doi.org/10.1109/access.2018.2841854.

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