Quantitative Phase Imaging and Artificial Intelligence: A Review
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Abstract (arXiv)
Recent advances in quantitative phase imaging (QPI) and artificial intelligence (AI) have opened up the possibility of an exciting frontier. The fast and label-free nature of QPI enables the rapid generation of large-scale and uniform-quality imaging data in two, three, and four dimensions. Subsequently, the AI-assisted interrogation of QPI data using data-driven machine learning techniques results in a variety of biomedical applications. Also, machine learning enhances QPI itself. Herein, we review the synergy between QPI and machine learning with a particular focus on deep learning. Further, we provide practical guidelines and perspectives for further development.
Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). First posted on arXiv 6 Jun 2018.
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Citing papers per year: 2021: 1; 2022: 6; 2023: 3; 2024: 3.
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- 2022Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imagingcited by 107
- 2022Fourier Imager Network (FIN): A deep neural network for hologram reconstruction with superior external generalizationcited by 18
- 2022Self-supervised learning of hologram reconstruction using physics consistencycited by 14
- 2023eFIN: Enhanced Fourier Imager Network for generalizable autofocusing and pixel super-resolution in holographic imagingcited by 8
- 2023Digital staining in optical microscopy using deep learning -- a reviewcited by 7
- 2022Diffractive Interconnects: All-Optical Permutation Operation Using Diffractive Networkscited by 6
- 2021Missing Cone Artifacts Removal in ODT using Unsupervised Deep Learning in Projection Domaincited by 3
- 2024Subwavelength Imaging using a Solid-Immersion Diffractive Optical Processorcited by 2
- 2024Multiplane Quantitative Phase Imaging Using a Wavelength-Multiplexed Diffractive Optical Processorcited by 2
- 2022From Hours to Seconds: Towards 100x Faster Quantitative Phase Imaging via Differentiable Microscopycited by 1
- 2022Outlier Detection using Self-Organizing Maps for Automated Blood Cell Analysiscited by 1
- 2023Calibration-free quantitative phase imaging in multi-core fiber endoscopes using end-to-end deep learningcited by 1
1 more
- 2024Prior-guided Diffusion Model for Cell Segmentation in Quantitative Phase Imaging10 May 2024
- 2024Multiplane Quantitative Phase Imaging Using a Wavelength-Multiplexed Diffractive Optical Processor16 Mar 2024
- 2024Subwavelength Imaging using a Solid-Immersion Diffractive Optical Processor17 Jan 2024
- 2023Calibration-free quantitative phase imaging in multi-core fiber endoscopes using end-to-end deep learning12 Dec 2023
- 2023Digital staining in optical microscopy using deep learning -- a review14 Mar 2023
- 2023eFIN: Enhanced Fourier Imager Network for generalizable autofocusing and pixel super-resolution in holographic imaging9 Jan 2023
- 2022Self-supervised learning of hologram reconstruction using physics consistency17 Sep 2022
- 2022Outlier Detection using Self-Organizing Maps for Automated Blood Cell Analysis18 Aug 2022
- 2022Diffractive Interconnects: All-Optical Permutation Operation Using Diffractive Networks21 Jun 2022
- 2022From Hours to Seconds: Towards 100x Faster Quantitative Phase Imaging via Differentiable Microscopy23 May 2022
- 2022Fourier Imager Network (FIN): A deep neural network for hologram reconstruction with superior external generalization22 Apr 2022
- 2022Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging10 Feb 2022
- 2022Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imagingcited by 107
- 2022Fourier Imager Network (FIN): A deep neural network for hologram reconstruction with superior external generalizationcited by 18
- 2022Self-supervised learning of hologram reconstruction using physics consistencycited by 14
- 2023eFIN: Enhanced Fourier Imager Network for generalizable autofocusing and pixel super-resolution in holographic imagingcited by 8
- 2023Digital staining in optical microscopy using deep learning -- a reviewcited by 7
- 2022Diffractive Interconnects: All-Optical Permutation Operation Using Diffractive Networkscited by 6
- 2021Missing Cone Artifacts Removal in ODT using Unsupervised Deep Learning in Projection Domaincited by 3
- 2024Subwavelength Imaging using a Solid-Immersion Diffractive Optical Processorcited by 2
- 2024Multiplane Quantitative Phase Imaging Using a Wavelength-Multiplexed Diffractive Optical Processorcited by 2
- 2022From Hours to Seconds: Towards 100x Faster Quantitative Phase Imaging via Differentiable Microscopycited by 1
- 2022Outlier Detection using Self-Organizing Maps for Automated Blood Cell Analysiscited by 1
- 2023Calibration-free quantitative phase imaging in multi-core fiber endoscopes using end-to-end deep learningcited by 1
- 2024Multiplane Quantitative Phase Imaging Using a Wavelength-Multiplexed Diffractive Optical Processor16 Mar 2024
- 2024Subwavelength Imaging using a Solid-Immersion Diffractive Optical Processor17 Jan 2024
- 2023Calibration-free quantitative phase imaging in multi-core fiber endoscopes using end-to-end deep learning12 Dec 2023
- 2023Digital staining in optical microscopy using deep learning -- a review14 Mar 2023
- 2023eFIN: Enhanced Fourier Imager Network for generalizable autofocusing and pixel super-resolution in holographic imaging9 Jan 2023
- 2022Self-supervised learning of hologram reconstruction using physics consistency17 Sep 2022
- 2022Outlier Detection using Self-Organizing Maps for Automated Blood Cell Analysis18 Aug 2022
- 2022Diffractive Interconnects: All-Optical Permutation Operation Using Diffractive Networks21 Jun 2022
- 2022From Hours to Seconds: Towards 100x Faster Quantitative Phase Imaging via Differentiable Microscopy23 May 2022
- 2022Fourier Imager Network (FIN): A deep neural network for hologram reconstruction with superior external generalization22 Apr 2022
- 2022Image-to-Image Regression with Distribution-Free Uncertainty Quantification and Applications in Imaging10 Feb 2022
- 2021Missing Cone Artifacts Removal in ODT using Unsupervised Deep Learning in Projection Domain16 Mar 2021