Deep learning in the phase extraction of electronic speckle pattern interferometry
W Jiang, T Ren, Q Fu - Electronics, 2024 - mdpi.com
Electronic speckle pattern interferometry (ESPI) is widely used in fields such as materials
science, biomedical research, surface morphology analysis, and optical component …
science, biomedical research, surface morphology analysis, and optical component …
Recent advances and current trends in transmission tomographic diffraction microscopy
Optical microscopy techniques are among the most used methods in biomedical sample
characterization. In their more advanced realization, optical microscopes demonstrate …
characterization. In their more advanced realization, optical microscopes demonstrate …
All-optical complex field imaging using diffractive processors
Complex field imaging, which captures both the amplitude and phase information of input
optical fields or objects, can offer rich structural insights into samples, such as their …
optical fields or objects, can offer rich structural insights into samples, such as their …
[HTML][HTML] Enhanced tissue slide imaging in the complex domain via cross-explainable GAN for Fourier ptychographic microscopy
Achieving microscopy with large space-bandwidth products plays a key role in diagnostic
imaging and is widely significant in the overall field of clinical practice. Among quantitative …
imaging and is widely significant in the overall field of clinical practice. Among quantitative …
Motion-resolved, reference-free holographic imaging via spatiotemporally regularized inversion
Holography is a powerful technique that records the amplitude and phase of an optical field
simultaneously, enabling a variety of applications such as label-free biomedical analysis …
simultaneously, enabling a variety of applications such as label-free biomedical analysis …
[HTML][HTML] Deep-ultraviolet Fourier ptychography (DUV-FP) for label-free biochemical imaging via feature-domain optimization
We present deep-ultraviolet Fourier ptychography (DUV-FP) for high-resolution chemical
imaging of biological specimens in their native state without exogenous stains. This …
imaging of biological specimens in their native state without exogenous stains. This …
Object detection, auto-focusing and transfer learning for digital holography of solid composite propellant using efficient neural network
G Xu, Y Huang, J Lyu, P Liu, W Ao - Optics and Lasers in Engineering, 2024 - Elsevier
Digital holography has emerged as a powerful tool for various applications. However,
applications such as target detection and depth prediction in complex scenarios like …
applications such as target detection and depth prediction in complex scenarios like …
Res-u2net: untrained deep learning for phase retrieval and image reconstruction
C Osorio Quero, D Leykam… - Journal of the Optical …, 2024 - opg.optica.org
Conventional deep learning-based image reconstruction methods require a large amount of
training data, which can be hard to obtain in practice. Untrained deep learning methods …
training data, which can be hard to obtain in practice. Untrained deep learning methods …
Single-shot inline holography using a physics-aware diffusion model
Among holographic imaging configurations, inline holography excels in its compact design
and portability, making it the preferred choice for on-site or field applications with unique …
and portability, making it the preferred choice for on-site or field applications with unique …
Deep learning phase recovery: data-driven, physics-driven, or a combination of both?
Phase recovery, calculating the phase of a light wave from its intensity measurements, is
essential for various applications, such as coherent diffraction imaging, adaptive optics, and …
essential for various applications, such as coherent diffraction imaging, adaptive optics, and …