Rapid quantitative interferometric microscopy using fast Fourier transform and differential–integral based phase retrieval algorithm (FFT-DI-PRA)
Phase retrieval in quantitative interferometric microscopy is a time-consuming and computationally expensive process, thus limiting the applications on cell dynamic detections. Here, we propose Fast Fourier Transform and Differential–Integral based Phase Retrieval Algorithm (FFT-DI-PRA) focusing on...
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| Published in | Optics communications Vol. 456; p. 124613 |
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| Main Authors | , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
01.02.2020
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0030-4018 1873-0310 |
| DOI | 10.1016/j.optcom.2019.124613 |
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| Abstract | Phase retrieval in quantitative interferometric microscopy is a time-consuming and computationally expensive process, thus limiting the applications on cell dynamic detections. Here, we propose Fast Fourier Transform and Differential–Integral based Phase Retrieval Algorithm (FFT-DI-PRA) focusing on quantitative cell phase imaging to significantly accelerate the phase retrieval process. The proposed method first obtains the wrapped phase from a single-shot interferogram using the FFT based phase extraction method; then, its phase derivatives are computed along two orthogonal directions; finally, the unwrapped specimen phase is reconstructed by phase integration from corrected phase derivatives. Since the FFT based phase extraction method can effectively suppress the noise, the phase wraps can be easily recognized in phase derivatives avoiding the noise influences, thus supporting the rapid and accurate phase wrapping. As a perfect combination of the FFT based phase extraction and the differential–integral based phase wrapping, FFT-DI-PRA only takes ∼0.03 second for phase imaging from one single-shot interferogram of 512×512 pixels using a typical desktop; moreover, it provides high-accurate specimen phase distributions as shown here by both simulations and experiments, suggesting that FFT-DI-PRA is an effective tool used in rapid quantitative live cell phase imaging and display. |
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| AbstractList | Phase retrieval in quantitative interferometric microscopy is a time-consuming and computationally expensive process, thus limiting the applications on cell dynamic detections. Here, we propose Fast Fourier Transform and Differential–Integral based Phase Retrieval Algorithm (FFT-DI-PRA) focusing on quantitative cell phase imaging to significantly accelerate the phase retrieval process. The proposed method first obtains the wrapped phase from a single-shot interferogram using the FFT based phase extraction method; then, its phase derivatives are computed along two orthogonal directions; finally, the unwrapped specimen phase is reconstructed by phase integration from corrected phase derivatives. Since the FFT based phase extraction method can effectively suppress the noise, the phase wraps can be easily recognized in phase derivatives avoiding the noise influences, thus supporting the rapid and accurate phase wrapping. As a perfect combination of the FFT based phase extraction and the differential–integral based phase wrapping, FFT-DI-PRA only takes ∼0.03 second for phase imaging from one single-shot interferogram of 512×512 pixels using a typical desktop; moreover, it provides high-accurate specimen phase distributions as shown here by both simulations and experiments, suggesting that FFT-DI-PRA is an effective tool used in rapid quantitative live cell phase imaging and display. |
| ArticleNumber | 124613 |
| Author | Wei, Qi Yu, Miao Liu, Fei Zhang, Mingyuan Vargas, Javier Wang, Shouyu Xue, Liang Liu, Cheng |
| Author_xml | – sequence: 1 givenname: Qi surname: Wei fullname: Wei, Qi organization: Computational Optics Laboratory, School of Science, Jiangnan University, Wuxi, Jiangsu 214122, China – sequence: 2 givenname: Mingyuan surname: Zhang fullname: Zhang, Mingyuan organization: Computational Optics Laboratory, School of Science, Jiangnan University, Wuxi, Jiangsu 214122, China – sequence: 3 givenname: Miao surname: Yu fullname: Yu, Miao organization: Computational Optics Laboratory, School of Science, Jiangnan University, Wuxi, Jiangsu 214122, China – sequence: 4 givenname: Liang surname: Xue fullname: Xue, Liang organization: College of Electronics and Information Engineering, Shanghai University of Electric Power, Shanghai 200090, China – sequence: 5 givenname: Cheng surname: Liu fullname: Liu, Cheng organization: Computational Optics Laboratory, School of Science, Jiangnan University, Wuxi, Jiangsu 214122, China – sequence: 6 givenname: Javier surname: Vargas fullname: Vargas, Javier organization: Faculty of Medicine, Department of Anatomy and Cell Biology, McGill University, Montreal, Quebec H3A0C7, Canada – sequence: 7 givenname: Fei surname: Liu fullname: Liu, Fei organization: Single Molecule Nanometry Laboratory (Sinmolab), Nanjing Agricultural University, Nanjing, Jiangsu, 210095, China – sequence: 8 givenname: Shouyu surname: Wang fullname: Wang, Shouyu email: shouyu@jiangnan.edu.cn organization: Computational Optics Laboratory, School of Science, Jiangnan University, Wuxi, Jiangsu 214122, China |
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