Abstract

Fourier ptychographic microscopy (FPM) is a newly developed microscopic technique for large field of view, high-resolution and quantitative phase imaging by combining the techniques from ptychographic imaging, aperture synthesizing and phase retrieval. In FPM, an LED array is utilized to illuminate the specimen from different angles and the corresponding intensity images are synthesized to reconstruct a high-resolution complex field. As a flexible and low-cost approach to achieve high-resolution, wide-field and quantitative phase imaging, FPM is of enormous potential in biomedical applications such as hematology and pathology. Conventionally, the FPM reconstruction problem is solved by using a phase retrieval method, termed Alternate Projection. By iteratively updating the Fourier spectrum with low-resolution-intensity images, the result converges to a high-resolution complex field. Here we propose a new FPM reconstruction framework with deep learning methods and design a multiscale, deep residual neural network for FPM reconstruction. We employ the widely used open-source deep learning library PyTorch to train and test our model and carefully choose the hyperparameters of our model. To train and analyze our model, we build a large-scale simulation dataset with an FPM imaging model and an actual dataset captured with an FPM system. The simulation dataset and actual dataset are separated as training datasets and test datasets, respectively. Our model is trained with the simulation training dataset and fine tuned with the fine-tune dataset, which contains actual training data. Both our model and the conventional method are tested on the simulation test dataset and the actual test dataset to evaluate the performances. We also show the reconstruction result of another neural network-based method for comparison. The experiments demonstrate that our model achieves better reconstruction results and consumes much less time than conventional methods. The results also point out that our model is more robust under system aberrations such as noise and blurring (fewer intensity images) compared with conventional methods.

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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References

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2018 (4)

J. Zhang, T. Xu, J. Liu, S. Chen, and X. Wang, “Precise Brightfield Localization Alignment for Fourier Ptychographic Microscopy,” IEEE Photonics J. 10, 1–13 (2018).
[Crossref]

J. Zhang, T. Xu, S. Chen, and X. Wang, “Efficient Colorful Fourier Ptychographic Microscopy Reconstruction with Wavelet Fusion,” IEEE Access 6, 31729–31739 (2018).
[Crossref]

T. Nguyen, Y. Xue, Y. Li, L. Tian, and G. Nehmetallah, “Deep learning approach for Fourier ptychography microscopy,” Opt. Express 26, 26470 (2018).
[Crossref] [PubMed]

S. Jiang, K. Guo, J. Liao, and G. Zheng, “Solving Fourier ptychographic imaging problems via neural network modeling and TensorFlow,” Biomed. Opt. Express 9, 3306 (2018).
[Crossref] [PubMed]

2017 (2)

Y. Rivenson, Y. Zhang, H. Gunaydin, D. Teng, and A. Ozcan, “Phase recovery and holographic image reconstruction using deep learning in neural networks,” Light. Sci. & Appl. 1, 1–30 (2017).

A. Sinha, J. Lee, S. Li, and G. Barbastathis, “Lensless computational imaging through deep learning,” Optica 4, 1117 (2017).
[Crossref]

2016 (4)

J. Holloway, M. S. Asif, M. K. Sharma, N. Matsuda, R. Horstmeyer, O. Cossairt, and A. Veeraraghavan, “Toward Long-Distance Subdiffraction Imaging Using Coherent Camera Arrays,” IEEE Transactions on Comput. Imaging 2, 251–265 (2016).
[Crossref]

S. Pacheco, G. Zheng, and R. Liang, “Reflective Fourier ptychography,” J. Biomed. Opt. 21, 026010 (2016).
[Crossref]

J. Sun, Q. Chen, Y. Zhang, and C. Zuo, “Efficient positional misalignment correction method for Fourier ptychographic microscopy,” Biomed. Opt. Express 7, 1336 (2016).
[Crossref] [PubMed]

K. Guo, S. Dong, and G. Zheng, “Fourier Ptychography for Brightfield, Phase, Darkfield, Reflective, Multi-Slice, and Fluorescence Imaging,” IEEE journal selected topics Quantam Electron. 22, 1–12 (2016).

2015 (10)

X. Ou, R. Horstmeyer, G. Zheng, and C. Yang, “High numerical aperture Fourier ptychography: principle, implementation and characterization,” Opt. Express 23, 3472 (2015).
[Crossref] [PubMed]

J. Chung, X. Ou, R. P. Kulkarni, and C. Yang, “Counting white blood cells from a blood smear using fourier ptychographic microscopy,” PLoS ONE 10, 1–10 (2015).
[Crossref]

R. Horstmeyer, X. Ou, G. Zheng, P. Willems, and C. Yang, “Digital pathology with Fourier ptychography,” Comput. Med. Imaging Graph. 42, 38–43 (2015).
[Crossref]

L. Tian and L. Waller, “3D intensity and phase imaging from light field measurements in an LED array microscope,” Optica 2, 104 (2015).
[Crossref]

L. Bian, J. Suo, G. Zheng, K. Guo, F. Chen, and Q. Dai, “Fourier ptychographic reconstruction using Wirtinger flow optimization,” Opt. Express 23, 4856 (2015).
[Crossref] [PubMed]

R. Horstmeyer, R. Y. Chen, X. Ou, B. Ames, J. A. Tropp, and C. Yang, “Solving ptychography with a convex relaxation,” New J. Phys. 17, 53044 (2015).
[Crossref]

W. Luo, A. Greenbaum, Y. Zhang, and A. Ozcan, “Synthetic aperture-based on-chip microscopy,” Light. Sci. & Appl. 4, e261 (2015).
[Crossref]

Y. Lecun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521, 436–444 (2015).
[Crossref] [PubMed]

J. Schmidhuber, “Deep Learning in neural networks: An overview,” Neural Networks 61, 85–117 (2015).
[Crossref]

L.-H. Yeh, J. Dong, J. Zhong, L. Tian, M. Chen, G. Tang, M. Soltanolkotabi, and L. Waller, “Experimental robustness of Fourier ptychography phase retrieval algorithms,” Opt. Express 23, 33214 (2015).
[Crossref]

2014 (8)

S. Dong, P. Nanda, R. Shiradkar, K. Guo, and G. Zheng, “High-resolution fluorescence imaging via pattern-illuminated Fourier ptychography,” Opt. Express 22, 20856 (2014).
[Crossref] [PubMed]

S. Dong, R. Horstmeyer, R. Shiradkar, K. Guo, X. Ou, Z. Bian, H. Xin, and G. Zheng, “Aperture-scanning Fourier ptychography for 3D refocusing and super-resolution macroscopic imaging,” Opt. Express 22, 13586 (2014).
[Crossref] [PubMed]

L. Bian, J. Suo, G. Situ, G. Zheng, F. Chen, and Q. Dai, “Content adaptive illumination for Fourier ptychography,” Opt. Lett. 39, 6648 (2014).
[Crossref] [PubMed]

S. Dong, R. Shiradkar, P. Nanda, and G. Zheng, “Spectral multiplexing and coherent-state decomposition in Fourier ptychographic imaging,” Biomed. Opt. Express 5, 1757 (2014).
[Crossref] [PubMed]

R. Horstmeyer, G. Zheng, X. Ou, and C. Yang, “Modeling extensions of fourier ptychographic microscopy,” Microsc. Microanal. 20, 370–371 (2014).
[Crossref]

X. Ou, G. Zheng, and C. Yang, “Embedded pupil function recovery for Fourier ptychographic microscopy,” Opt. Express 22, 4960 (2014).
[Crossref] [PubMed]

A. Williams, J. Chung, X. Ou, G. Zheng, S. Rawal, Z. Ao, R. Datar, C. Yang, and R. Cote, “Fourier ptychographic microscopy for filtration-based circulating tumor cell enumeration and analysis,” J. Biomed. Opt. 19, 066007 (2014).
[Crossref] [PubMed]

L. Tian, X. Li, K. Ramchandran, and L. Waller, “Multiplexed coded illumination for Fourier Ptychography with an LED array microscope,” Biomed. Opt. Express 5, 2376 (2014).
[Crossref] [PubMed]

2013 (4)

G. Zheng, R. Horstmeyer, and C. Yang, “Wide-field, high-resolution Fourier ptychographic microscopy,” Nat. Photonics 7, 739–745 (2013).
[Crossref]

X. Ou, R. Horstmeyer, C. Yang, and G. Zheng, “Quantitative phase imaging via Fourier ptychographic microscopy,” Opt. Lett. 38, 4845–4848 (2013).
[Crossref] [PubMed]

Z. Bian, S. Dong, and G. Zheng, “Adaptive system correction for robust Fourier ptychographic imaging,” Opt. Express 21, 32400 (2013).
[Crossref]

I. Waldspurger, A. D’Aspremont, and S. Mallat, “Phase recovery, MaxCut and complex semidefinite programming,” Math. Program. 149, 47–81 (2013).
[Crossref]

2010 (1)

T. Gutzler, T. R. Hillman, S. A. Alexandrov, and D. D. Sampson, “Coherent aperture-synthesis, wide-field, high-resolution holographic microscopy of biological tissue,” Opt. Lett. 35, 1136–1138 (2010).
[Crossref] [PubMed]

2009 (2)

T. R. Hillman, T. Gutzler, S. A. Alexandrov, and D. D. Sampson, “High-resolution, wide-field object reconstruction with synthetic aperture Fourier holographic optical microscopy,” Opt. Express 17, 7873–7892 (2009).
[Crossref] [PubMed]

A. M. Maiden and J. M. Rodenburg, “An improved ptychographical phase retrieval algorithm for diffractive imaging,” Ultramicroscopy 109, 1256–1262 (2009).
[Crossref] [PubMed]

2008 (1)

J. M. Rodenburg, “Ptychography and related diffractive imaging methods,” Adv. Imaging Electron Phys. 150, 87–184 (2008).
[Crossref]

2007 (1)

J. M. Rodenburg, A. C. Hurst, A. G. Cullis, B. R. Dobson, F. Pfeiffer, O. Bunk, C. David, K. Jefimovs, and I. Johnson, “Hard-X-ray lensless imaging of extended objects,” Phys. Rev. Lett. 98, 17–21 (2007).
[Crossref]

2006 (1)

V. Mico, Z. Zalevsky, P. García-Martínez, and J. García, “Synthetic aperture superresolution with multiple off-axis holograms,” J. Opt. Soc. Am. A 23, 3162–3170 (2006).
[Crossref]

2004 (1)

H. M. Faulkner and J. M. Rodenburg, “Movable aperture lensless transmission microscopy: A novel phase retrieval algorithm,” Phys. Rev. Lett. 93, 023903 (2004).
[Crossref] [PubMed]

1982 (1)

J. R. Fienup, “Phase retrieval algorithms: a comparison,” Appl. Opt. 21, 2758 (1982).
[Crossref] [PubMed]

Acosta, A.

C. Ledig, L. Theis, F. Huszar, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi, “Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2017), pp. 105–114.

Aitken, A.

C. Ledig, L. Theis, F. Huszar, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi, “Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2017), pp. 105–114.

Alexandrov, S. A.

T. Gutzler, T. R. Hillman, S. A. Alexandrov, and D. D. Sampson, “Coherent aperture-synthesis, wide-field, high-resolution holographic microscopy of biological tissue,” Opt. Lett. 35, 1136–1138 (2010).
[Crossref] [PubMed]

T. R. Hillman, T. Gutzler, S. A. Alexandrov, and D. D. Sampson, “High-resolution, wide-field object reconstruction with synthetic aperture Fourier holographic optical microscopy,” Opt. Express 17, 7873–7892 (2009).
[Crossref] [PubMed]

Ames, B.

R. Horstmeyer, R. Y. Chen, X. Ou, B. Ames, J. A. Tropp, and C. Yang, “Solving ptychography with a convex relaxation,” New J. Phys. 17, 53044 (2015).
[Crossref]

Ao, Z.

A. Williams, J. Chung, X. Ou, G. Zheng, S. Rawal, Z. Ao, R. Datar, C. Yang, and R. Cote, “Fourier ptychographic microscopy for filtration-based circulating tumor cell enumeration and analysis,” J. Biomed. Opt. 19, 066007 (2014).
[Crossref] [PubMed]

Asif, M. S.

J. Holloway, M. S. Asif, M. K. Sharma, N. Matsuda, R. Horstmeyer, O. Cossairt, and A. Veeraraghavan, “Toward Long-Distance Subdiffraction Imaging Using Coherent Camera Arrays,” IEEE Transactions on Comput. Imaging 2, 251–265 (2016).
[Crossref]

Barbastathis, G.

A. Sinha, J. Lee, S. Li, and G. Barbastathis, “Lensless computational imaging through deep learning,” Optica 4, 1117 (2017).
[Crossref]

Bengio, Y.

Y. Lecun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521, 436–444 (2015).
[Crossref] [PubMed]

Bian, L.

L. Bian, J. Suo, G. Zheng, K. Guo, F. Chen, and Q. Dai, “Fourier ptychographic reconstruction using Wirtinger flow optimization,” Opt. Express 23, 4856 (2015).
[Crossref] [PubMed]

L. Bian, J. Suo, G. Situ, G. Zheng, F. Chen, and Q. Dai, “Content adaptive illumination for Fourier ptychography,” Opt. Lett. 39, 6648 (2014).
[Crossref] [PubMed]

Bian, Z.

S. Dong, R. Horstmeyer, R. Shiradkar, K. Guo, X. Ou, Z. Bian, H. Xin, and G. Zheng, “Aperture-scanning Fourier ptychography for 3D refocusing and super-resolution macroscopic imaging,” Opt. Express 22, 13586 (2014).
[Crossref] [PubMed]

Z. Bian, S. Dong, and G. Zheng, “Adaptive system correction for robust Fourier ptychographic imaging,” Opt. Express 21, 32400 (2013).
[Crossref]

Bunk, O.

J. M. Rodenburg, A. C. Hurst, A. G. Cullis, B. R. Dobson, F. Pfeiffer, O. Bunk, C. David, K. Jefimovs, and I. Johnson, “Hard-X-ray lensless imaging of extended objects,” Phys. Rev. Lett. 98, 17–21 (2007).
[Crossref]

Caballero, J.

C. Ledig, L. Theis, F. Huszar, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi, “Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2017), pp. 105–114.

Carone, D.

Y. F. Cheng, M. Strachan, Z. Weiss, M. Deb, D. Carone, and V. Ganapati, “Illumination pattern design with deep learning for single-shot fourier ptychographic microscopy,” arXiv preprint arXiv:1810.03481 (2018).

Chen, F.

L. Bian, J. Suo, G. Zheng, K. Guo, F. Chen, and Q. Dai, “Fourier ptychographic reconstruction using Wirtinger flow optimization,” Opt. Express 23, 4856 (2015).
[Crossref] [PubMed]

L. Bian, J. Suo, G. Situ, G. Zheng, F. Chen, and Q. Dai, “Content adaptive illumination for Fourier ptychography,” Opt. Lett. 39, 6648 (2014).
[Crossref] [PubMed]

Chen, M.

L.-H. Yeh, J. Dong, J. Zhong, L. Tian, M. Chen, G. Tang, M. Soltanolkotabi, and L. Waller, “Experimental robustness of Fourier ptychography phase retrieval algorithms,” Opt. Express 23, 33214 (2015).
[Crossref]

Chen, Q.

J. Sun, Q. Chen, Y. Zhang, and C. Zuo, “Efficient positional misalignment correction method for Fourier ptychographic microscopy,” Biomed. Opt. Express 7, 1336 (2016).
[Crossref] [PubMed]

Chen, R. Y.

R. Horstmeyer, R. Y. Chen, X. Ou, B. Ames, J. A. Tropp, and C. Yang, “Solving ptychography with a convex relaxation,” New J. Phys. 17, 53044 (2015).
[Crossref]

Chen, S.

J. Zhang, T. Xu, J. Liu, S. Chen, and X. Wang, “Precise Brightfield Localization Alignment for Fourier Ptychographic Microscopy,” IEEE Photonics J. 10, 1–13 (2018).
[Crossref]

J. Zhang, T. Xu, S. Chen, and X. Wang, “Efficient Colorful Fourier Ptychographic Microscopy Reconstruction with Wavelet Fusion,” IEEE Access 6, 31729–31739 (2018).
[Crossref]

Cheng, Y. F.

Y. F. Cheng, M. Strachan, Z. Weiss, M. Deb, D. Carone, and V. Ganapati, “Illumination pattern design with deep learning for single-shot fourier ptychographic microscopy,” arXiv preprint arXiv:1810.03481 (2018).

Chung, J.

J. Chung, X. Ou, R. P. Kulkarni, and C. Yang, “Counting white blood cells from a blood smear using fourier ptychographic microscopy,” PLoS ONE 10, 1–10 (2015).
[Crossref]

A. Williams, J. Chung, X. Ou, G. Zheng, S. Rawal, Z. Ao, R. Datar, C. Yang, and R. Cote, “Fourier ptychographic microscopy for filtration-based circulating tumor cell enumeration and analysis,” J. Biomed. Opt. 19, 066007 (2014).
[Crossref] [PubMed]

Cossairt, O.

J. Holloway, M. S. Asif, M. K. Sharma, N. Matsuda, R. Horstmeyer, O. Cossairt, and A. Veeraraghavan, “Toward Long-Distance Subdiffraction Imaging Using Coherent Camera Arrays,” IEEE Transactions on Comput. Imaging 2, 251–265 (2016).
[Crossref]

A. Kappeler, S. Ghosh, J. Holloway, O. Cossairt, and A. Katsaggelos, “Ptychnet: CNN based fourier ptychography,” in IEEE International Conference on Image Processing (ICIP), (IEEE, 2017), pp. 1712–1716.

Cote, R.

A. Williams, J. Chung, X. Ou, G. Zheng, S. Rawal, Z. Ao, R. Datar, C. Yang, and R. Cote, “Fourier ptychographic microscopy for filtration-based circulating tumor cell enumeration and analysis,” J. Biomed. Opt. 19, 066007 (2014).
[Crossref] [PubMed]

Cullis, A. G.

J. M. Rodenburg, A. C. Hurst, A. G. Cullis, B. R. Dobson, F. Pfeiffer, O. Bunk, C. David, K. Jefimovs, and I. Johnson, “Hard-X-ray lensless imaging of extended objects,” Phys. Rev. Lett. 98, 17–21 (2007).
[Crossref]

Cunningham, A.

C. Ledig, L. Theis, F. Huszar, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi, “Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2017), pp. 105–114.

D’Aspremont, A.

I. Waldspurger, A. D’Aspremont, and S. Mallat, “Phase recovery, MaxCut and complex semidefinite programming,” Math. Program. 149, 47–81 (2013).
[Crossref]

Dai, Q.

L. Bian, J. Suo, G. Zheng, K. Guo, F. Chen, and Q. Dai, “Fourier ptychographic reconstruction using Wirtinger flow optimization,” Opt. Express 23, 4856 (2015).
[Crossref] [PubMed]

L. Bian, J. Suo, G. Situ, G. Zheng, F. Chen, and Q. Dai, “Content adaptive illumination for Fourier ptychography,” Opt. Lett. 39, 6648 (2014).
[Crossref] [PubMed]

Datar, R.

A. Williams, J. Chung, X. Ou, G. Zheng, S. Rawal, Z. Ao, R. Datar, C. Yang, and R. Cote, “Fourier ptychographic microscopy for filtration-based circulating tumor cell enumeration and analysis,” J. Biomed. Opt. 19, 066007 (2014).
[Crossref] [PubMed]

David, C.

J. M. Rodenburg, A. C. Hurst, A. G. Cullis, B. R. Dobson, F. Pfeiffer, O. Bunk, C. David, K. Jefimovs, and I. Johnson, “Hard-X-ray lensless imaging of extended objects,” Phys. Rev. Lett. 98, 17–21 (2007).
[Crossref]

Deb, M.

Y. F. Cheng, M. Strachan, Z. Weiss, M. Deb, D. Carone, and V. Ganapati, “Illumination pattern design with deep learning for single-shot fourier ptychographic microscopy,” arXiv preprint arXiv:1810.03481 (2018).

Dobson, B. R.

J. M. Rodenburg, A. C. Hurst, A. G. Cullis, B. R. Dobson, F. Pfeiffer, O. Bunk, C. David, K. Jefimovs, and I. Johnson, “Hard-X-ray lensless imaging of extended objects,” Phys. Rev. Lett. 98, 17–21 (2007).
[Crossref]

Dong, C.

C. Dong, C. C. Loy, K. He, and X. Tang, “Learning a Deep Convolutional Network for Image Super-Resolution,” in Proceedings of the European conference on computer vision (ECCV), vol. 8689 (2014), pp. 184–199.

Dong, J.

L.-H. Yeh, J. Dong, J. Zhong, L. Tian, M. Chen, G. Tang, M. Soltanolkotabi, and L. Waller, “Experimental robustness of Fourier ptychography phase retrieval algorithms,” Opt. Express 23, 33214 (2015).
[Crossref]

Dong, S.

K. Guo, S. Dong, and G. Zheng, “Fourier Ptychography for Brightfield, Phase, Darkfield, Reflective, Multi-Slice, and Fluorescence Imaging,” IEEE journal selected topics Quantam Electron. 22, 1–12 (2016).

S. Dong, P. Nanda, R. Shiradkar, K. Guo, and G. Zheng, “High-resolution fluorescence imaging via pattern-illuminated Fourier ptychography,” Opt. Express 22, 20856 (2014).
[Crossref] [PubMed]

S. Dong, R. Horstmeyer, R. Shiradkar, K. Guo, X. Ou, Z. Bian, H. Xin, and G. Zheng, “Aperture-scanning Fourier ptychography for 3D refocusing and super-resolution macroscopic imaging,” Opt. Express 22, 13586 (2014).
[Crossref] [PubMed]

S. Dong, R. Shiradkar, P. Nanda, and G. Zheng, “Spectral multiplexing and coherent-state decomposition in Fourier ptychographic imaging,” Biomed. Opt. Express 5, 1757 (2014).
[Crossref] [PubMed]

Z. Bian, S. Dong, and G. Zheng, “Adaptive system correction for robust Fourier ptychographic imaging,” Opt. Express 21, 32400 (2013).
[Crossref]

Faulkner, H. M.

H. M. Faulkner and J. M. Rodenburg, “Movable aperture lensless transmission microscopy: A novel phase retrieval algorithm,” Phys. Rev. Lett. 93, 023903 (2004).
[Crossref] [PubMed]

Fienup, J. R.

J. R. Fienup, “Phase retrieval algorithms: a comparison,” Appl. Opt. 21, 2758 (1982).
[Crossref] [PubMed]

Ganapati, V.

Y. F. Cheng, M. Strachan, Z. Weiss, M. Deb, D. Carone, and V. Ganapati, “Illumination pattern design with deep learning for single-shot fourier ptychographic microscopy,” arXiv preprint arXiv:1810.03481 (2018).

García, J.

V. Mico, Z. Zalevsky, P. García-Martínez, and J. García, “Synthetic aperture superresolution with multiple off-axis holograms,” J. Opt. Soc. Am. A 23, 3162–3170 (2006).
[Crossref]

García-Martínez, P.

V. Mico, Z. Zalevsky, P. García-Martínez, and J. García, “Synthetic aperture superresolution with multiple off-axis holograms,” J. Opt. Soc. Am. A 23, 3162–3170 (2006).
[Crossref]

Ghosh, S.

A. Kappeler, S. Ghosh, J. Holloway, O. Cossairt, and A. Katsaggelos, “Ptychnet: CNN based fourier ptychography,” in IEEE International Conference on Image Processing (ICIP), (IEEE, 2017), pp. 1712–1716.

Greenbaum, A.

W. Luo, A. Greenbaum, Y. Zhang, and A. Ozcan, “Synthetic aperture-based on-chip microscopy,” Light. Sci. & Appl. 4, e261 (2015).
[Crossref]

Gunaydin, H.

Y. Rivenson, Y. Zhang, H. Gunaydin, D. Teng, and A. Ozcan, “Phase recovery and holographic image reconstruction using deep learning in neural networks,” Light. Sci. & Appl. 1, 1–30 (2017).

Guo, K.

S. Jiang, K. Guo, J. Liao, and G. Zheng, “Solving Fourier ptychographic imaging problems via neural network modeling and TensorFlow,” Biomed. Opt. Express 9, 3306 (2018).
[Crossref] [PubMed]

K. Guo, S. Dong, and G. Zheng, “Fourier Ptychography for Brightfield, Phase, Darkfield, Reflective, Multi-Slice, and Fluorescence Imaging,” IEEE journal selected topics Quantam Electron. 22, 1–12 (2016).

L. Bian, J. Suo, G. Zheng, K. Guo, F. Chen, and Q. Dai, “Fourier ptychographic reconstruction using Wirtinger flow optimization,” Opt. Express 23, 4856 (2015).
[Crossref] [PubMed]

S. Dong, P. Nanda, R. Shiradkar, K. Guo, and G. Zheng, “High-resolution fluorescence imaging via pattern-illuminated Fourier ptychography,” Opt. Express 22, 20856 (2014).
[Crossref] [PubMed]

S. Dong, R. Horstmeyer, R. Shiradkar, K. Guo, X. Ou, Z. Bian, H. Xin, and G. Zheng, “Aperture-scanning Fourier ptychography for 3D refocusing and super-resolution macroscopic imaging,” Opt. Express 22, 13586 (2014).
[Crossref] [PubMed]

Gutzler, T.

T. Gutzler, T. R. Hillman, S. A. Alexandrov, and D. D. Sampson, “Coherent aperture-synthesis, wide-field, high-resolution holographic microscopy of biological tissue,” Opt. Lett. 35, 1136–1138 (2010).
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T. R. Hillman, T. Gutzler, S. A. Alexandrov, and D. D. Sampson, “High-resolution, wide-field object reconstruction with synthetic aperture Fourier holographic optical microscopy,” Opt. Express 17, 7873–7892 (2009).
[Crossref] [PubMed]

He, K.

K. He, X. Zhang, S. Ren, and J. Sun, “Deep Residual Learning for Image Recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2016), pp. 770–778.

C. Dong, C. C. Loy, K. He, and X. Tang, “Learning a Deep Convolutional Network for Image Super-Resolution,” in Proceedings of the European conference on computer vision (ECCV), vol. 8689 (2014), pp. 184–199.

Hillman, T. R.

T. Gutzler, T. R. Hillman, S. A. Alexandrov, and D. D. Sampson, “Coherent aperture-synthesis, wide-field, high-resolution holographic microscopy of biological tissue,” Opt. Lett. 35, 1136–1138 (2010).
[Crossref] [PubMed]

T. R. Hillman, T. Gutzler, S. A. Alexandrov, and D. D. Sampson, “High-resolution, wide-field object reconstruction with synthetic aperture Fourier holographic optical microscopy,” Opt. Express 17, 7873–7892 (2009).
[Crossref] [PubMed]

Hinton, G.

Y. Lecun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521, 436–444 (2015).
[Crossref] [PubMed]

Holloway, J.

J. Holloway, M. S. Asif, M. K. Sharma, N. Matsuda, R. Horstmeyer, O. Cossairt, and A. Veeraraghavan, “Toward Long-Distance Subdiffraction Imaging Using Coherent Camera Arrays,” IEEE Transactions on Comput. Imaging 2, 251–265 (2016).
[Crossref]

A. Kappeler, S. Ghosh, J. Holloway, O. Cossairt, and A. Katsaggelos, “Ptychnet: CNN based fourier ptychography,” in IEEE International Conference on Image Processing (ICIP), (IEEE, 2017), pp. 1712–1716.

Horstmeyer, R.

J. Holloway, M. S. Asif, M. K. Sharma, N. Matsuda, R. Horstmeyer, O. Cossairt, and A. Veeraraghavan, “Toward Long-Distance Subdiffraction Imaging Using Coherent Camera Arrays,” IEEE Transactions on Comput. Imaging 2, 251–265 (2016).
[Crossref]

R. Horstmeyer, R. Y. Chen, X. Ou, B. Ames, J. A. Tropp, and C. Yang, “Solving ptychography with a convex relaxation,” New J. Phys. 17, 53044 (2015).
[Crossref]

X. Ou, R. Horstmeyer, G. Zheng, and C. Yang, “High numerical aperture Fourier ptychography: principle, implementation and characterization,” Opt. Express 23, 3472 (2015).
[Crossref] [PubMed]

R. Horstmeyer, X. Ou, G. Zheng, P. Willems, and C. Yang, “Digital pathology with Fourier ptychography,” Comput. Med. Imaging Graph. 42, 38–43 (2015).
[Crossref]

R. Horstmeyer, G. Zheng, X. Ou, and C. Yang, “Modeling extensions of fourier ptychographic microscopy,” Microsc. Microanal. 20, 370–371 (2014).
[Crossref]

S. Dong, R. Horstmeyer, R. Shiradkar, K. Guo, X. Ou, Z. Bian, H. Xin, and G. Zheng, “Aperture-scanning Fourier ptychography for 3D refocusing and super-resolution macroscopic imaging,” Opt. Express 22, 13586 (2014).
[Crossref] [PubMed]

G. Zheng, R. Horstmeyer, and C. Yang, “Wide-field, high-resolution Fourier ptychographic microscopy,” Nat. Photonics 7, 739–745 (2013).
[Crossref]

X. Ou, R. Horstmeyer, C. Yang, and G. Zheng, “Quantitative phase imaging via Fourier ptychographic microscopy,” Opt. Lett. 38, 4845–4848 (2013).
[Crossref] [PubMed]

Hurst, A. C.

J. M. Rodenburg, A. C. Hurst, A. G. Cullis, B. R. Dobson, F. Pfeiffer, O. Bunk, C. David, K. Jefimovs, and I. Johnson, “Hard-X-ray lensless imaging of extended objects,” Phys. Rev. Lett. 98, 17–21 (2007).
[Crossref]

Huszar, F.

C. Ledig, L. Theis, F. Huszar, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi, “Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2017), pp. 105–114.

Jefimovs, K.

J. M. Rodenburg, A. C. Hurst, A. G. Cullis, B. R. Dobson, F. Pfeiffer, O. Bunk, C. David, K. Jefimovs, and I. Johnson, “Hard-X-ray lensless imaging of extended objects,” Phys. Rev. Lett. 98, 17–21 (2007).
[Crossref]

Jiang, S.

S. Jiang, K. Guo, J. Liao, and G. Zheng, “Solving Fourier ptychographic imaging problems via neural network modeling and TensorFlow,” Biomed. Opt. Express 9, 3306 (2018).
[Crossref] [PubMed]

Johnson, I.

J. M. Rodenburg, A. C. Hurst, A. G. Cullis, B. R. Dobson, F. Pfeiffer, O. Bunk, C. David, K. Jefimovs, and I. Johnson, “Hard-X-ray lensless imaging of extended objects,” Phys. Rev. Lett. 98, 17–21 (2007).
[Crossref]

Kappeler, A.

A. Kappeler, S. Ghosh, J. Holloway, O. Cossairt, and A. Katsaggelos, “Ptychnet: CNN based fourier ptychography,” in IEEE International Conference on Image Processing (ICIP), (IEEE, 2017), pp. 1712–1716.

Katsaggelos, A.

A. Kappeler, S. Ghosh, J. Holloway, O. Cossairt, and A. Katsaggelos, “Ptychnet: CNN based fourier ptychography,” in IEEE International Conference on Image Processing (ICIP), (IEEE, 2017), pp. 1712–1716.

Kim, H.

B. Lim, S. Son, H. Kim, S. Nah, and K. M. Lee, “Enhanced Deep Residual Networks for Single Image Super-Resolution,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), vol. 2017-July (IEEE, 2017), pp. 1132–1140.

Kim, J.

J. Kim, J. K. Lee, and K. M. Lee, “Accurate Image Super-Resolution Using Very Deep Convolutional Networks,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2016), pp. 1646–1654.

Kulkarni, R. P.

J. Chung, X. Ou, R. P. Kulkarni, and C. Yang, “Counting white blood cells from a blood smear using fourier ptychographic microscopy,” PLoS ONE 10, 1–10 (2015).
[Crossref]

Lecun, Y.

Y. Lecun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521, 436–444 (2015).
[Crossref] [PubMed]

Ledig, C.

C. Ledig, L. Theis, F. Huszar, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi, “Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2017), pp. 105–114.

Lee, J.

A. Sinha, J. Lee, S. Li, and G. Barbastathis, “Lensless computational imaging through deep learning,” Optica 4, 1117 (2017).
[Crossref]

Lee, J. K.

J. Kim, J. K. Lee, and K. M. Lee, “Accurate Image Super-Resolution Using Very Deep Convolutional Networks,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2016), pp. 1646–1654.

Lee, K. M.

J. Kim, J. K. Lee, and K. M. Lee, “Accurate Image Super-Resolution Using Very Deep Convolutional Networks,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2016), pp. 1646–1654.

B. Lim, S. Son, H. Kim, S. Nah, and K. M. Lee, “Enhanced Deep Residual Networks for Single Image Super-Resolution,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), vol. 2017-July (IEEE, 2017), pp. 1132–1140.

Li, S.

A. Sinha, J. Lee, S. Li, and G. Barbastathis, “Lensless computational imaging through deep learning,” Optica 4, 1117 (2017).
[Crossref]

Li, X.

L. Tian, X. Li, K. Ramchandran, and L. Waller, “Multiplexed coded illumination for Fourier Ptychography with an LED array microscope,” Biomed. Opt. Express 5, 2376 (2014).
[Crossref] [PubMed]

Li, Y.

T. Nguyen, Y. Xue, Y. Li, L. Tian, and G. Nehmetallah, “Deep learning approach for Fourier ptychography microscopy,” Opt. Express 26, 26470 (2018).
[Crossref] [PubMed]

Liang, R.

S. Pacheco, G. Zheng, and R. Liang, “Reflective Fourier ptychography,” J. Biomed. Opt. 21, 026010 (2016).
[Crossref]

Liao, J.

S. Jiang, K. Guo, J. Liao, and G. Zheng, “Solving Fourier ptychographic imaging problems via neural network modeling and TensorFlow,” Biomed. Opt. Express 9, 3306 (2018).
[Crossref] [PubMed]

Lim, B.

B. Lim, S. Son, H. Kim, S. Nah, and K. M. Lee, “Enhanced Deep Residual Networks for Single Image Super-Resolution,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), vol. 2017-July (IEEE, 2017), pp. 1132–1140.

Liu, J.

J. Zhang, T. Xu, J. Liu, S. Chen, and X. Wang, “Precise Brightfield Localization Alignment for Fourier Ptychographic Microscopy,” IEEE Photonics J. 10, 1–13 (2018).
[Crossref]

Liu, X.

Y. Tai, J. Yang, and X. Liu, “Image Super-Resolution via Deep Recursive Residual Network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 2017-Janua (IEEE, 2017), pp. 2790–2798.

Loy, C. C.

C. Dong, C. C. Loy, K. He, and X. Tang, “Learning a Deep Convolutional Network for Image Super-Resolution,” in Proceedings of the European conference on computer vision (ECCV), vol. 8689 (2014), pp. 184–199.

Luo, W.

W. Luo, A. Greenbaum, Y. Zhang, and A. Ozcan, “Synthetic aperture-based on-chip microscopy,” Light. Sci. & Appl. 4, e261 (2015).
[Crossref]

Maiden, A. M.

A. M. Maiden and J. M. Rodenburg, “An improved ptychographical phase retrieval algorithm for diffractive imaging,” Ultramicroscopy 109, 1256–1262 (2009).
[Crossref] [PubMed]

Mallat, S.

I. Waldspurger, A. D’Aspremont, and S. Mallat, “Phase recovery, MaxCut and complex semidefinite programming,” Math. Program. 149, 47–81 (2013).
[Crossref]

Matsuda, N.

J. Holloway, M. S. Asif, M. K. Sharma, N. Matsuda, R. Horstmeyer, O. Cossairt, and A. Veeraraghavan, “Toward Long-Distance Subdiffraction Imaging Using Coherent Camera Arrays,” IEEE Transactions on Comput. Imaging 2, 251–265 (2016).
[Crossref]

Mico, V.

V. Mico, Z. Zalevsky, P. García-Martínez, and J. García, “Synthetic aperture superresolution with multiple off-axis holograms,” J. Opt. Soc. Am. A 23, 3162–3170 (2006).
[Crossref]

Nah, S.

B. Lim, S. Son, H. Kim, S. Nah, and K. M. Lee, “Enhanced Deep Residual Networks for Single Image Super-Resolution,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), vol. 2017-July (IEEE, 2017), pp. 1132–1140.

Nanda, P.

S. Dong, P. Nanda, R. Shiradkar, K. Guo, and G. Zheng, “High-resolution fluorescence imaging via pattern-illuminated Fourier ptychography,” Opt. Express 22, 20856 (2014).
[Crossref] [PubMed]

S. Dong, R. Shiradkar, P. Nanda, and G. Zheng, “Spectral multiplexing and coherent-state decomposition in Fourier ptychographic imaging,” Biomed. Opt. Express 5, 1757 (2014).
[Crossref] [PubMed]

Nehmetallah, G.

T. Nguyen, Y. Xue, Y. Li, L. Tian, and G. Nehmetallah, “Deep learning approach for Fourier ptychography microscopy,” Opt. Express 26, 26470 (2018).
[Crossref] [PubMed]

Nguyen, T.

T. Nguyen, Y. Xue, Y. Li, L. Tian, and G. Nehmetallah, “Deep learning approach for Fourier ptychography microscopy,” Opt. Express 26, 26470 (2018).
[Crossref] [PubMed]

Ou, X.

R. Horstmeyer, R. Y. Chen, X. Ou, B. Ames, J. A. Tropp, and C. Yang, “Solving ptychography with a convex relaxation,” New J. Phys. 17, 53044 (2015).
[Crossref]

X. Ou, R. Horstmeyer, G. Zheng, and C. Yang, “High numerical aperture Fourier ptychography: principle, implementation and characterization,” Opt. Express 23, 3472 (2015).
[Crossref] [PubMed]

J. Chung, X. Ou, R. P. Kulkarni, and C. Yang, “Counting white blood cells from a blood smear using fourier ptychographic microscopy,” PLoS ONE 10, 1–10 (2015).
[Crossref]

R. Horstmeyer, X. Ou, G. Zheng, P. Willems, and C. Yang, “Digital pathology with Fourier ptychography,” Comput. Med. Imaging Graph. 42, 38–43 (2015).
[Crossref]

A. Williams, J. Chung, X. Ou, G. Zheng, S. Rawal, Z. Ao, R. Datar, C. Yang, and R. Cote, “Fourier ptychographic microscopy for filtration-based circulating tumor cell enumeration and analysis,” J. Biomed. Opt. 19, 066007 (2014).
[Crossref] [PubMed]

X. Ou, G. Zheng, and C. Yang, “Embedded pupil function recovery for Fourier ptychographic microscopy,” Opt. Express 22, 4960 (2014).
[Crossref] [PubMed]

S. Dong, R. Horstmeyer, R. Shiradkar, K. Guo, X. Ou, Z. Bian, H. Xin, and G. Zheng, “Aperture-scanning Fourier ptychography for 3D refocusing and super-resolution macroscopic imaging,” Opt. Express 22, 13586 (2014).
[Crossref] [PubMed]

R. Horstmeyer, G. Zheng, X. Ou, and C. Yang, “Modeling extensions of fourier ptychographic microscopy,” Microsc. Microanal. 20, 370–371 (2014).
[Crossref]

X. Ou, R. Horstmeyer, C. Yang, and G. Zheng, “Quantitative phase imaging via Fourier ptychographic microscopy,” Opt. Lett. 38, 4845–4848 (2013).
[Crossref] [PubMed]

Ozcan, A.

Y. Rivenson, Y. Zhang, H. Gunaydin, D. Teng, and A. Ozcan, “Phase recovery and holographic image reconstruction using deep learning in neural networks,” Light. Sci. & Appl. 1, 1–30 (2017).

W. Luo, A. Greenbaum, Y. Zhang, and A. Ozcan, “Synthetic aperture-based on-chip microscopy,” Light. Sci. & Appl. 4, e261 (2015).
[Crossref]

Pacheco, S.

S. Pacheco, G. Zheng, and R. Liang, “Reflective Fourier ptychography,” J. Biomed. Opt. 21, 026010 (2016).
[Crossref]

Pfeiffer, F.

J. M. Rodenburg, A. C. Hurst, A. G. Cullis, B. R. Dobson, F. Pfeiffer, O. Bunk, C. David, K. Jefimovs, and I. Johnson, “Hard-X-ray lensless imaging of extended objects,” Phys. Rev. Lett. 98, 17–21 (2007).
[Crossref]

Ramchandran, K.

L. Tian, X. Li, K. Ramchandran, and L. Waller, “Multiplexed coded illumination for Fourier Ptychography with an LED array microscope,” Biomed. Opt. Express 5, 2376 (2014).
[Crossref] [PubMed]

Rawal, S.

A. Williams, J. Chung, X. Ou, G. Zheng, S. Rawal, Z. Ao, R. Datar, C. Yang, and R. Cote, “Fourier ptychographic microscopy for filtration-based circulating tumor cell enumeration and analysis,” J. Biomed. Opt. 19, 066007 (2014).
[Crossref] [PubMed]

Ren, S.

K. He, X. Zhang, S. Ren, and J. Sun, “Deep Residual Learning for Image Recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2016), pp. 770–778.

Rivenson, Y.

Y. Rivenson, Y. Zhang, H. Gunaydin, D. Teng, and A. Ozcan, “Phase recovery and holographic image reconstruction using deep learning in neural networks,” Light. Sci. & Appl. 1, 1–30 (2017).

Rodenburg, J. M.

A. M. Maiden and J. M. Rodenburg, “An improved ptychographical phase retrieval algorithm for diffractive imaging,” Ultramicroscopy 109, 1256–1262 (2009).
[Crossref] [PubMed]

J. M. Rodenburg, “Ptychography and related diffractive imaging methods,” Adv. Imaging Electron Phys. 150, 87–184 (2008).
[Crossref]

J. M. Rodenburg, A. C. Hurst, A. G. Cullis, B. R. Dobson, F. Pfeiffer, O. Bunk, C. David, K. Jefimovs, and I. Johnson, “Hard-X-ray lensless imaging of extended objects,” Phys. Rev. Lett. 98, 17–21 (2007).
[Crossref]

H. M. Faulkner and J. M. Rodenburg, “Movable aperture lensless transmission microscopy: A novel phase retrieval algorithm,” Phys. Rev. Lett. 93, 023903 (2004).
[Crossref] [PubMed]

Sampson, D. D.

T. Gutzler, T. R. Hillman, S. A. Alexandrov, and D. D. Sampson, “Coherent aperture-synthesis, wide-field, high-resolution holographic microscopy of biological tissue,” Opt. Lett. 35, 1136–1138 (2010).
[Crossref] [PubMed]

T. R. Hillman, T. Gutzler, S. A. Alexandrov, and D. D. Sampson, “High-resolution, wide-field object reconstruction with synthetic aperture Fourier holographic optical microscopy,” Opt. Express 17, 7873–7892 (2009).
[Crossref] [PubMed]

Schmidhuber, J.

J. Schmidhuber, “Deep Learning in neural networks: An overview,” Neural Networks 61, 85–117 (2015).
[Crossref]

Sharma, M. K.

J. Holloway, M. S. Asif, M. K. Sharma, N. Matsuda, R. Horstmeyer, O. Cossairt, and A. Veeraraghavan, “Toward Long-Distance Subdiffraction Imaging Using Coherent Camera Arrays,” IEEE Transactions on Comput. Imaging 2, 251–265 (2016).
[Crossref]

Shi, W.

C. Ledig, L. Theis, F. Huszar, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi, “Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2017), pp. 105–114.

Shiradkar, R.

S. Dong, P. Nanda, R. Shiradkar, K. Guo, and G. Zheng, “High-resolution fluorescence imaging via pattern-illuminated Fourier ptychography,” Opt. Express 22, 20856 (2014).
[Crossref] [PubMed]

S. Dong, R. Horstmeyer, R. Shiradkar, K. Guo, X. Ou, Z. Bian, H. Xin, and G. Zheng, “Aperture-scanning Fourier ptychography for 3D refocusing and super-resolution macroscopic imaging,” Opt. Express 22, 13586 (2014).
[Crossref] [PubMed]

S. Dong, R. Shiradkar, P. Nanda, and G. Zheng, “Spectral multiplexing and coherent-state decomposition in Fourier ptychographic imaging,” Biomed. Opt. Express 5, 1757 (2014).
[Crossref] [PubMed]

Sinha, A.

A. Sinha, J. Lee, S. Li, and G. Barbastathis, “Lensless computational imaging through deep learning,” Optica 4, 1117 (2017).
[Crossref]

Situ, G.

L. Bian, J. Suo, G. Situ, G. Zheng, F. Chen, and Q. Dai, “Content adaptive illumination for Fourier ptychography,” Opt. Lett. 39, 6648 (2014).
[Crossref] [PubMed]

Soltanolkotabi, M.

L.-H. Yeh, J. Dong, J. Zhong, L. Tian, M. Chen, G. Tang, M. Soltanolkotabi, and L. Waller, “Experimental robustness of Fourier ptychography phase retrieval algorithms,” Opt. Express 23, 33214 (2015).
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Son, S.

B. Lim, S. Son, H. Kim, S. Nah, and K. M. Lee, “Enhanced Deep Residual Networks for Single Image Super-Resolution,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), vol. 2017-July (IEEE, 2017), pp. 1132–1140.

Strachan, M.

Y. F. Cheng, M. Strachan, Z. Weiss, M. Deb, D. Carone, and V. Ganapati, “Illumination pattern design with deep learning for single-shot fourier ptychographic microscopy,” arXiv preprint arXiv:1810.03481 (2018).

Sun, J.

J. Sun, Q. Chen, Y. Zhang, and C. Zuo, “Efficient positional misalignment correction method for Fourier ptychographic microscopy,” Biomed. Opt. Express 7, 1336 (2016).
[Crossref] [PubMed]

K. He, X. Zhang, S. Ren, and J. Sun, “Deep Residual Learning for Image Recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2016), pp. 770–778.

Suo, J.

L. Bian, J. Suo, G. Zheng, K. Guo, F. Chen, and Q. Dai, “Fourier ptychographic reconstruction using Wirtinger flow optimization,” Opt. Express 23, 4856 (2015).
[Crossref] [PubMed]

L. Bian, J. Suo, G. Situ, G. Zheng, F. Chen, and Q. Dai, “Content adaptive illumination for Fourier ptychography,” Opt. Lett. 39, 6648 (2014).
[Crossref] [PubMed]

Tai, Y.

Y. Tai, J. Yang, and X. Liu, “Image Super-Resolution via Deep Recursive Residual Network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 2017-Janua (IEEE, 2017), pp. 2790–2798.

Tang, G.

L.-H. Yeh, J. Dong, J. Zhong, L. Tian, M. Chen, G. Tang, M. Soltanolkotabi, and L. Waller, “Experimental robustness of Fourier ptychography phase retrieval algorithms,” Opt. Express 23, 33214 (2015).
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Tang, X.

C. Dong, C. C. Loy, K. He, and X. Tang, “Learning a Deep Convolutional Network for Image Super-Resolution,” in Proceedings of the European conference on computer vision (ECCV), vol. 8689 (2014), pp. 184–199.

Tejani, A.

C. Ledig, L. Theis, F. Huszar, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi, “Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2017), pp. 105–114.

Teng, D.

Y. Rivenson, Y. Zhang, H. Gunaydin, D. Teng, and A. Ozcan, “Phase recovery and holographic image reconstruction using deep learning in neural networks,” Light. Sci. & Appl. 1, 1–30 (2017).

Theis, L.

C. Ledig, L. Theis, F. Huszar, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi, “Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2017), pp. 105–114.

Tian, L.

T. Nguyen, Y. Xue, Y. Li, L. Tian, and G. Nehmetallah, “Deep learning approach for Fourier ptychography microscopy,” Opt. Express 26, 26470 (2018).
[Crossref] [PubMed]

L.-H. Yeh, J. Dong, J. Zhong, L. Tian, M. Chen, G. Tang, M. Soltanolkotabi, and L. Waller, “Experimental robustness of Fourier ptychography phase retrieval algorithms,” Opt. Express 23, 33214 (2015).
[Crossref]

L. Tian and L. Waller, “3D intensity and phase imaging from light field measurements in an LED array microscope,” Optica 2, 104 (2015).
[Crossref]

L. Tian, X. Li, K. Ramchandran, and L. Waller, “Multiplexed coded illumination for Fourier Ptychography with an LED array microscope,” Biomed. Opt. Express 5, 2376 (2014).
[Crossref] [PubMed]

Totz, J.

C. Ledig, L. Theis, F. Huszar, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi, “Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2017), pp. 105–114.

Tropp, J. A.

R. Horstmeyer, R. Y. Chen, X. Ou, B. Ames, J. A. Tropp, and C. Yang, “Solving ptychography with a convex relaxation,” New J. Phys. 17, 53044 (2015).
[Crossref]

Veeraraghavan, A.

J. Holloway, M. S. Asif, M. K. Sharma, N. Matsuda, R. Horstmeyer, O. Cossairt, and A. Veeraraghavan, “Toward Long-Distance Subdiffraction Imaging Using Coherent Camera Arrays,” IEEE Transactions on Comput. Imaging 2, 251–265 (2016).
[Crossref]

Waldspurger, I.

I. Waldspurger, A. D’Aspremont, and S. Mallat, “Phase recovery, MaxCut and complex semidefinite programming,” Math. Program. 149, 47–81 (2013).
[Crossref]

Waller, L.

L. Tian and L. Waller, “3D intensity and phase imaging from light field measurements in an LED array microscope,” Optica 2, 104 (2015).
[Crossref]

L.-H. Yeh, J. Dong, J. Zhong, L. Tian, M. Chen, G. Tang, M. Soltanolkotabi, and L. Waller, “Experimental robustness of Fourier ptychography phase retrieval algorithms,” Opt. Express 23, 33214 (2015).
[Crossref]

L. Tian, X. Li, K. Ramchandran, and L. Waller, “Multiplexed coded illumination for Fourier Ptychography with an LED array microscope,” Biomed. Opt. Express 5, 2376 (2014).
[Crossref] [PubMed]

Wang, X.

J. Zhang, T. Xu, J. Liu, S. Chen, and X. Wang, “Precise Brightfield Localization Alignment for Fourier Ptychographic Microscopy,” IEEE Photonics J. 10, 1–13 (2018).
[Crossref]

J. Zhang, T. Xu, S. Chen, and X. Wang, “Efficient Colorful Fourier Ptychographic Microscopy Reconstruction with Wavelet Fusion,” IEEE Access 6, 31729–31739 (2018).
[Crossref]

Wang, Z.

C. Ledig, L. Theis, F. Huszar, J. Caballero, A. Cunningham, A. Acosta, A. Aitken, A. Tejani, J. Totz, Z. Wang, and W. Shi, “Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2017), pp. 105–114.

Weiss, Z.

Y. F. Cheng, M. Strachan, Z. Weiss, M. Deb, D. Carone, and V. Ganapati, “Illumination pattern design with deep learning for single-shot fourier ptychographic microscopy,” arXiv preprint arXiv:1810.03481 (2018).

Willems, P.

R. Horstmeyer, X. Ou, G. Zheng, P. Willems, and C. Yang, “Digital pathology with Fourier ptychography,” Comput. Med. Imaging Graph. 42, 38–43 (2015).
[Crossref]

Williams, A.

A. Williams, J. Chung, X. Ou, G. Zheng, S. Rawal, Z. Ao, R. Datar, C. Yang, and R. Cote, “Fourier ptychographic microscopy for filtration-based circulating tumor cell enumeration and analysis,” J. Biomed. Opt. 19, 066007 (2014).
[Crossref] [PubMed]

Xin, H.

S. Dong, R. Horstmeyer, R. Shiradkar, K. Guo, X. Ou, Z. Bian, H. Xin, and G. Zheng, “Aperture-scanning Fourier ptychography for 3D refocusing and super-resolution macroscopic imaging,” Opt. Express 22, 13586 (2014).
[Crossref] [PubMed]

Xu, T.

J. Zhang, T. Xu, S. Chen, and X. Wang, “Efficient Colorful Fourier Ptychographic Microscopy Reconstruction with Wavelet Fusion,” IEEE Access 6, 31729–31739 (2018).
[Crossref]

J. Zhang, T. Xu, J. Liu, S. Chen, and X. Wang, “Precise Brightfield Localization Alignment for Fourier Ptychographic Microscopy,” IEEE Photonics J. 10, 1–13 (2018).
[Crossref]

Xue, Y.

T. Nguyen, Y. Xue, Y. Li, L. Tian, and G. Nehmetallah, “Deep learning approach for Fourier ptychography microscopy,” Opt. Express 26, 26470 (2018).
[Crossref] [PubMed]

Yang, C.

R. Horstmeyer, R. Y. Chen, X. Ou, B. Ames, J. A. Tropp, and C. Yang, “Solving ptychography with a convex relaxation,” New J. Phys. 17, 53044 (2015).
[Crossref]

X. Ou, R. Horstmeyer, G. Zheng, and C. Yang, “High numerical aperture Fourier ptychography: principle, implementation and characterization,” Opt. Express 23, 3472 (2015).
[Crossref] [PubMed]

J. Chung, X. Ou, R. P. Kulkarni, and C. Yang, “Counting white blood cells from a blood smear using fourier ptychographic microscopy,” PLoS ONE 10, 1–10 (2015).
[Crossref]

R. Horstmeyer, X. Ou, G. Zheng, P. Willems, and C. Yang, “Digital pathology with Fourier ptychography,” Comput. Med. Imaging Graph. 42, 38–43 (2015).
[Crossref]

X. Ou, G. Zheng, and C. Yang, “Embedded pupil function recovery for Fourier ptychographic microscopy,” Opt. Express 22, 4960 (2014).
[Crossref] [PubMed]

A. Williams, J. Chung, X. Ou, G. Zheng, S. Rawal, Z. Ao, R. Datar, C. Yang, and R. Cote, “Fourier ptychographic microscopy for filtration-based circulating tumor cell enumeration and analysis,” J. Biomed. Opt. 19, 066007 (2014).
[Crossref] [PubMed]

R. Horstmeyer, G. Zheng, X. Ou, and C. Yang, “Modeling extensions of fourier ptychographic microscopy,” Microsc. Microanal. 20, 370–371 (2014).
[Crossref]

X. Ou, R. Horstmeyer, C. Yang, and G. Zheng, “Quantitative phase imaging via Fourier ptychographic microscopy,” Opt. Lett. 38, 4845–4848 (2013).
[Crossref] [PubMed]

G. Zheng, R. Horstmeyer, and C. Yang, “Wide-field, high-resolution Fourier ptychographic microscopy,” Nat. Photonics 7, 739–745 (2013).
[Crossref]

Yang, J.

Y. Tai, J. Yang, and X. Liu, “Image Super-Resolution via Deep Recursive Residual Network,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), vol. 2017-Janua (IEEE, 2017), pp. 2790–2798.

Yeh, L.-H.

L.-H. Yeh, J. Dong, J. Zhong, L. Tian, M. Chen, G. Tang, M. Soltanolkotabi, and L. Waller, “Experimental robustness of Fourier ptychography phase retrieval algorithms,” Opt. Express 23, 33214 (2015).
[Crossref]

Zalevsky, Z.

V. Mico, Z. Zalevsky, P. García-Martínez, and J. García, “Synthetic aperture superresolution with multiple off-axis holograms,” J. Opt. Soc. Am. A 23, 3162–3170 (2006).
[Crossref]

Zhang, J.

J. Zhang, T. Xu, S. Chen, and X. Wang, “Efficient Colorful Fourier Ptychographic Microscopy Reconstruction with Wavelet Fusion,” IEEE Access 6, 31729–31739 (2018).
[Crossref]

J. Zhang, T. Xu, J. Liu, S. Chen, and X. Wang, “Precise Brightfield Localization Alignment for Fourier Ptychographic Microscopy,” IEEE Photonics J. 10, 1–13 (2018).
[Crossref]

Zhang, X.

K. He, X. Zhang, S. Ren, and J. Sun, “Deep Residual Learning for Image Recognition,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), (IEEE, 2016), pp. 770–778.

Zhang, Y.

Y. Rivenson, Y. Zhang, H. Gunaydin, D. Teng, and A. Ozcan, “Phase recovery and holographic image reconstruction using deep learning in neural networks,” Light. Sci. & Appl. 1, 1–30 (2017).

J. Sun, Q. Chen, Y. Zhang, and C. Zuo, “Efficient positional misalignment correction method for Fourier ptychographic microscopy,” Biomed. Opt. Express 7, 1336 (2016).
[Crossref] [PubMed]

W. Luo, A. Greenbaum, Y. Zhang, and A. Ozcan, “Synthetic aperture-based on-chip microscopy,” Light. Sci. & Appl. 4, e261 (2015).
[Crossref]

Zheng, G.

S. Jiang, K. Guo, J. Liao, and G. Zheng, “Solving Fourier ptychographic imaging problems via neural network modeling and TensorFlow,” Biomed. Opt. Express 9, 3306 (2018).
[Crossref] [PubMed]

S. Pacheco, G. Zheng, and R. Liang, “Reflective Fourier ptychography,” J. Biomed. Opt. 21, 026010 (2016).
[Crossref]

K. Guo, S. Dong, and G. Zheng, “Fourier Ptychography for Brightfield, Phase, Darkfield, Reflective, Multi-Slice, and Fluorescence Imaging,” IEEE journal selected topics Quantam Electron. 22, 1–12 (2016).

R. Horstmeyer, X. Ou, G. Zheng, P. Willems, and C. Yang, “Digital pathology with Fourier ptychography,” Comput. Med. Imaging Graph. 42, 38–43 (2015).
[Crossref]

X. Ou, R. Horstmeyer, G. Zheng, and C. Yang, “High numerical aperture Fourier ptychography: principle, implementation and characterization,” Opt. Express 23, 3472 (2015).
[Crossref] [PubMed]

L. Bian, J. Suo, G. Zheng, K. Guo, F. Chen, and Q. Dai, “Fourier ptychographic reconstruction using Wirtinger flow optimization,” Opt. Express 23, 4856 (2015).
[Crossref] [PubMed]

R. Horstmeyer, G. Zheng, X. Ou, and C. Yang, “Modeling extensions of fourier ptychographic microscopy,” Microsc. Microanal. 20, 370–371 (2014).
[Crossref]

L. Bian, J. Suo, G. Situ, G. Zheng, F. Chen, and Q. Dai, “Content adaptive illumination for Fourier ptychography,” Opt. Lett. 39, 6648 (2014).
[Crossref] [PubMed]

S. Dong, R. Shiradkar, P. Nanda, and G. Zheng, “Spectral multiplexing and coherent-state decomposition in Fourier ptychographic imaging,” Biomed. Opt. Express 5, 1757 (2014).
[Crossref] [PubMed]

S. Dong, P. Nanda, R. Shiradkar, K. Guo, and G. Zheng, “High-resolution fluorescence imaging via pattern-illuminated Fourier ptychography,” Opt. Express 22, 20856 (2014).
[Crossref] [PubMed]

S. Dong, R. Horstmeyer, R. Shiradkar, K. Guo, X. Ou, Z. Bian, H. Xin, and G. Zheng, “Aperture-scanning Fourier ptychography for 3D refocusing and super-resolution macroscopic imaging,” Opt. Express 22, 13586 (2014).
[Crossref] [PubMed]

A. Williams, J. Chung, X. Ou, G. Zheng, S. Rawal, Z. Ao, R. Datar, C. Yang, and R. Cote, “Fourier ptychographic microscopy for filtration-based circulating tumor cell enumeration and analysis,” J. Biomed. Opt. 19, 066007 (2014).
[Crossref] [PubMed]

X. Ou, G. Zheng, and C. Yang, “Embedded pupil function recovery for Fourier ptychographic microscopy,” Opt. Express 22, 4960 (2014).
[Crossref] [PubMed]

Z. Bian, S. Dong, and G. Zheng, “Adaptive system correction for robust Fourier ptychographic imaging,” Opt. Express 21, 32400 (2013).
[Crossref]

G. Zheng, R. Horstmeyer, and C. Yang, “Wide-field, high-resolution Fourier ptychographic microscopy,” Nat. Photonics 7, 739–745 (2013).
[Crossref]

X. Ou, R. Horstmeyer, C. Yang, and G. Zheng, “Quantitative phase imaging via Fourier ptychographic microscopy,” Opt. Lett. 38, 4845–4848 (2013).
[Crossref] [PubMed]

Zhong, J.

L.-H. Yeh, J. Dong, J. Zhong, L. Tian, M. Chen, G. Tang, M. Soltanolkotabi, and L. Waller, “Experimental robustness of Fourier ptychography phase retrieval algorithms,” Opt. Express 23, 33214 (2015).
[Crossref]

Zuo, C.

J. Sun, Q. Chen, Y. Zhang, and C. Zuo, “Efficient positional misalignment correction method for Fourier ptychographic microscopy,” Biomed. Opt. Express 7, 1336 (2016).
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Adv. Imaging Electron Phys. (1)

J. M. Rodenburg, “Ptychography and related diffractive imaging methods,” Adv. Imaging Electron Phys. 150, 87–184 (2008).
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Appl. Opt. (1)

J. R. Fienup, “Phase retrieval algorithms: a comparison,” Appl. Opt. 21, 2758 (1982).
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Biomed. Opt. Express (4)

L. Tian, X. Li, K. Ramchandran, and L. Waller, “Multiplexed coded illumination for Fourier Ptychography with an LED array microscope,” Biomed. Opt. Express 5, 2376 (2014).
[Crossref] [PubMed]

J. Sun, Q. Chen, Y. Zhang, and C. Zuo, “Efficient positional misalignment correction method for Fourier ptychographic microscopy,” Biomed. Opt. Express 7, 1336 (2016).
[Crossref] [PubMed]

S. Dong, R. Shiradkar, P. Nanda, and G. Zheng, “Spectral multiplexing and coherent-state decomposition in Fourier ptychographic imaging,” Biomed. Opt. Express 5, 1757 (2014).
[Crossref] [PubMed]

S. Jiang, K. Guo, J. Liao, and G. Zheng, “Solving Fourier ptychographic imaging problems via neural network modeling and TensorFlow,” Biomed. Opt. Express 9, 3306 (2018).
[Crossref] [PubMed]

Comput. Med. Imaging Graph. (1)

R. Horstmeyer, X. Ou, G. Zheng, P. Willems, and C. Yang, “Digital pathology with Fourier ptychography,” Comput. Med. Imaging Graph. 42, 38–43 (2015).
[Crossref]

IEEE Access (1)

J. Zhang, T. Xu, S. Chen, and X. Wang, “Efficient Colorful Fourier Ptychographic Microscopy Reconstruction with Wavelet Fusion,” IEEE Access 6, 31729–31739 (2018).
[Crossref]

IEEE journal selected topics Quantam Electron. (1)

K. Guo, S. Dong, and G. Zheng, “Fourier Ptychography for Brightfield, Phase, Darkfield, Reflective, Multi-Slice, and Fluorescence Imaging,” IEEE journal selected topics Quantam Electron. 22, 1–12 (2016).

IEEE Photonics J. (1)

J. Zhang, T. Xu, J. Liu, S. Chen, and X. Wang, “Precise Brightfield Localization Alignment for Fourier Ptychographic Microscopy,” IEEE Photonics J. 10, 1–13 (2018).
[Crossref]

IEEE Transactions on Comput. Imaging (1)

J. Holloway, M. S. Asif, M. K. Sharma, N. Matsuda, R. Horstmeyer, O. Cossairt, and A. Veeraraghavan, “Toward Long-Distance Subdiffraction Imaging Using Coherent Camera Arrays,” IEEE Transactions on Comput. Imaging 2, 251–265 (2016).
[Crossref]

J. Biomed. Opt. (2)

A. Williams, J. Chung, X. Ou, G. Zheng, S. Rawal, Z. Ao, R. Datar, C. Yang, and R. Cote, “Fourier ptychographic microscopy for filtration-based circulating tumor cell enumeration and analysis,” J. Biomed. Opt. 19, 066007 (2014).
[Crossref] [PubMed]

S. Pacheco, G. Zheng, and R. Liang, “Reflective Fourier ptychography,” J. Biomed. Opt. 21, 026010 (2016).
[Crossref]

J. Opt. Soc. Am. A (1)

V. Mico, Z. Zalevsky, P. García-Martínez, and J. García, “Synthetic aperture superresolution with multiple off-axis holograms,” J. Opt. Soc. Am. A 23, 3162–3170 (2006).
[Crossref]

Light. Sci. & Appl. (2)

W. Luo, A. Greenbaum, Y. Zhang, and A. Ozcan, “Synthetic aperture-based on-chip microscopy,” Light. Sci. & Appl. 4, e261 (2015).
[Crossref]

Y. Rivenson, Y. Zhang, H. Gunaydin, D. Teng, and A. Ozcan, “Phase recovery and holographic image reconstruction using deep learning in neural networks,” Light. Sci. & Appl. 1, 1–30 (2017).

Math. Program. (1)

I. Waldspurger, A. D’Aspremont, and S. Mallat, “Phase recovery, MaxCut and complex semidefinite programming,” Math. Program. 149, 47–81 (2013).
[Crossref]

Microsc. Microanal. (1)

R. Horstmeyer, G. Zheng, X. Ou, and C. Yang, “Modeling extensions of fourier ptychographic microscopy,” Microsc. Microanal. 20, 370–371 (2014).
[Crossref]

Nat. Photonics (1)

G. Zheng, R. Horstmeyer, and C. Yang, “Wide-field, high-resolution Fourier ptychographic microscopy,” Nat. Photonics 7, 739–745 (2013).
[Crossref]

Nature (1)

Y. Lecun, Y. Bengio, and G. Hinton, “Deep learning,” Nature 521, 436–444 (2015).
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Neural Networks (1)

J. Schmidhuber, “Deep Learning in neural networks: An overview,” Neural Networks 61, 85–117 (2015).
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New J. Phys. (1)

R. Horstmeyer, R. Y. Chen, X. Ou, B. Ames, J. A. Tropp, and C. Yang, “Solving ptychography with a convex relaxation,” New J. Phys. 17, 53044 (2015).
[Crossref]

Opt. Express (9)

S. Dong, P. Nanda, R. Shiradkar, K. Guo, and G. Zheng, “High-resolution fluorescence imaging via pattern-illuminated Fourier ptychography,” Opt. Express 22, 20856 (2014).
[Crossref] [PubMed]

S. Dong, R. Horstmeyer, R. Shiradkar, K. Guo, X. Ou, Z. Bian, H. Xin, and G. Zheng, “Aperture-scanning Fourier ptychography for 3D refocusing and super-resolution macroscopic imaging,” Opt. Express 22, 13586 (2014).
[Crossref] [PubMed]

T. Nguyen, Y. Xue, Y. Li, L. Tian, and G. Nehmetallah, “Deep learning approach for Fourier ptychography microscopy,” Opt. Express 26, 26470 (2018).
[Crossref] [PubMed]

L.-H. Yeh, J. Dong, J. Zhong, L. Tian, M. Chen, G. Tang, M. Soltanolkotabi, and L. Waller, “Experimental robustness of Fourier ptychography phase retrieval algorithms,” Opt. Express 23, 33214 (2015).
[Crossref]

L. Bian, J. Suo, G. Zheng, K. Guo, F. Chen, and Q. Dai, “Fourier ptychographic reconstruction using Wirtinger flow optimization,” Opt. Express 23, 4856 (2015).
[Crossref] [PubMed]

X. Ou, R. Horstmeyer, G. Zheng, and C. Yang, “High numerical aperture Fourier ptychography: principle, implementation and characterization,” Opt. Express 23, 3472 (2015).
[Crossref] [PubMed]

X. Ou, G. Zheng, and C. Yang, “Embedded pupil function recovery for Fourier ptychographic microscopy,” Opt. Express 22, 4960 (2014).
[Crossref] [PubMed]

Z. Bian, S. Dong, and G. Zheng, “Adaptive system correction for robust Fourier ptychographic imaging,” Opt. Express 21, 32400 (2013).
[Crossref]

T. R. Hillman, T. Gutzler, S. A. Alexandrov, and D. D. Sampson, “High-resolution, wide-field object reconstruction with synthetic aperture Fourier holographic optical microscopy,” Opt. Express 17, 7873–7892 (2009).
[Crossref] [PubMed]

Opt. Lett. (3)

T. Gutzler, T. R. Hillman, S. A. Alexandrov, and D. D. Sampson, “Coherent aperture-synthesis, wide-field, high-resolution holographic microscopy of biological tissue,” Opt. Lett. 35, 1136–1138 (2010).
[Crossref] [PubMed]

X. Ou, R. Horstmeyer, C. Yang, and G. Zheng, “Quantitative phase imaging via Fourier ptychographic microscopy,” Opt. Lett. 38, 4845–4848 (2013).
[Crossref] [PubMed]

L. Bian, J. Suo, G. Situ, G. Zheng, F. Chen, and Q. Dai, “Content adaptive illumination for Fourier ptychography,” Opt. Lett. 39, 6648 (2014).
[Crossref] [PubMed]

Optica (2)

L. Tian and L. Waller, “3D intensity and phase imaging from light field measurements in an LED array microscope,” Optica 2, 104 (2015).
[Crossref]

A. Sinha, J. Lee, S. Li, and G. Barbastathis, “Lensless computational imaging through deep learning,” Optica 4, 1117 (2017).
[Crossref]

Phys. Rev. Lett. (2)

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Figures (8)

Fig. 1
Fig. 1 Schematic diagram of FPM. (a) The system setup of a FPM. (b) The reconstruction process of FPM.
Fig. 2
Fig. 2 Differences between direct input and synthetic input.
Fig. 3
Fig. 3 An example of how to build and use the training dataset.
Fig. 4
Fig. 4 Model architecture of FPNN. The architecture of a residual block and the architecture of an upsample module are shown on the right side.
Fig. 5
Fig. 5 Evaluation of reconstruction results under a series of noise levels. (a)–(c) show the L1 loss, PSNR and SSIM of reconstructed intensity images under noise. (d)–(f) show the L1 loss, PSNR and SSIM of reconstructed phase images under noise.
Fig. 6
Fig. 6 Example reconstruction results of AP, FPNN and Shaowei Jiang’s method on the simulation test dataset. Gaussian distribution noises with zero mean and standard deviation of 1 × 10−4, 2 × 10−4 and 3 × 10−4 are added on group 1, 2 and 3.
Fig. 7
Fig. 7 Evaluation of reconstruction results with fewer intensity images. (a)–(c) show the L1 loss, PSNR and SSIM of reconstruction results respectively. The L1 loss, PSNR and SSIM of AP are always measured with 169 images.
Fig. 8
Fig. 8 Example reconstruction results of AP and FPNN on actual dataset.

Tables (1)

Tables Icon

Table 1 Time consumption of reconstructing a patch

Equations (7)

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k l = ( sin θ x l λ , sin θ y l λ ) ( l = 1 , 2 , , N LED ) ,
{ o ( r ) exp ( i k l r ) } = O ( k k l )
I lc ( r ) = | g lc ( r ) | 2 = | 1 { P ( k ) O ( k k l ) } | 2 ,
g le ( r ) = F 1 { P ( k ) O e ( k k l ) } ,
P ( k ) O e ( k k l ) = F { I lc ( r ) | g le ( r ) | g le ( r ) } .
P ( k ) O i ( k k l ) = F { I lc ( r ) } .
o i ( r ) = 1 { O i ( k ) } .

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