All-optical complex field imaging using diffractive processors

Light Science & Applications, Journal Year: 2024, Volume and Issue: 13(1)

Published: May 28, 2024

Language: Английский

---

Insights into infrared crystal phase characteristics based on deep learning holography with attention residual network

Journal of Materials Chemistry A, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 1, 2025

Through a synergistic blend of infrared digital holography and deep learning, we introduce unconventional mechanistic insight, namely the crystal phase.

Language: Английский

---

Computational microscopy with coherent diffractive imaging and ptychography

Nature, Journal Year: 2025, Volume and Issue: 637(8045), P. 281 - 295

Published: Jan. 8, 2025

Language: Английский

---

Deep Learning in the Phase Extraction of Electronic Speckle Pattern Interferometry

Electronics, Journal Year: 2024, Volume and Issue: 13(2), P. 418 - 418

Published: Jan. 19, 2024

Electronic speckle pattern interferometry (ESPI) is widely used in fields such as materials science, biomedical research, surface morphology analysis, and optical component inspection because of its high measurement accuracy, broad frequency range, ease measurement. Phase extraction a critical stage ESPI. However, conventional phase methods exhibit problems low slow processing speed, poor generalization. With the continuous development deep learning image processing, application from electronic images has become topic research. This paper reviews principles characteristics ESPI comprehensively analyzes processes for fringe patterns wrapped maps. The application, advantages, limitations techniques filtering, skeleton line extraction, unwrapping algorithms are discussed based on representation results. Finally, this provides perspective future trends, construction physical models interferometry, improvement optimization models, quantitative evaluation quality, field.

Language: Английский

---

Deep empirical neural network for optical phase retrieval over a scattering medium

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: Feb. 5, 2025

Abstract Supervised learning, a popular tool in modern science and technology, thrives on huge amounts of labeled data. Physics-enhanced deep neural networks offer an effective solution to alleviate the data burden by incorporating analytical model that interprets underlying physical processes. However, it completely fails tackling systems without solution, where wave scattering with multiple input output are typical examples. Herein, we propose concept empirical network (DENN) is hybridization model, which enables seeing through opaque medium untrained manner. The DENN does not rely data, all while delivering as high 58% improvement fidelity compared supervised learning using 30000 pairs for achieving same goal optical phase retrieval. might shed new light applications physics, information science, biology, chemistry beyond.

Language: Английский

---

Tailoring spatiotemporal wavepackets via two-dimensional space-time duality

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: March 21, 2025

Spatiotemporal (ST) beams—ultrafast optical wavepackets with customized spatial and temporal characteristics—present a significant contrast to conventional spatial-structured light hold the potential revolutionize our understanding manipulation of light. However, progress in ST beam research has been constrained by absence universal framework for its analysis generation. Here, we introduce concept 'two-dimensional space-time duality', establishing foundational duality between beams. We show that breaking exact balance paraxial diffraction narrow-band dispersion is crucial guiding dynamics wavepackets. Leveraging this insight, pioneer versatile complex-amplitude modulation strategy, enabling precise crafting beams an exceptional fidelity exceeding 97%. Furthermore, uncover new range harnessing one-to-one relationship scalar Our results expand toolkit promise applications across diverse spectrum wave-based physical systems. differ from standard structured The authors 2D spacetime conventional–spatiotemporal connection, development high-fidelity spatiotemporal

Language: Английский

---

Single-shot inline holography using a physics-aware diffusion model

Optics Express, Journal Year: 2024, Volume and Issue: 32(6), P. 10444 - 10444

Published: Feb. 27, 2024

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 requirements. However, effectively reconstruction from a single-shot measurement remains challenge. While several approaches have been proposed, our novel unsupervised algorithm, physics-aware diffusion model digital (PadDH), offers distinct advantages. By seamlessly integrating physical information pre-trained model, PadDH overcomes need training dataset significantly reduces number of parameters involved. Through comprehensive experiments using both synthetic experimental data, we validate capabilities reducing twin-image contamination generating high-quality reconstructions. Our work represents significant advancements by harnessing full potential prior.

Language: Английский

---

Enhanced tissue slide imaging in the complex domain via cross-explainable GAN for Fourier ptychographic microscopy

Computers in Biology and Medicine, Journal Year: 2024, Volume and Issue: 179, P. 108861 - 108861

Published: July 16, 2024

Achieving microscopy with large space-bandwidth products plays a key role in diagnostic imaging and is widely significant the overall field of clinical practice. Among quantitative techniques, Fourier Ptychography (FP) provides wide view high-resolution images, suitable to histopathological field, but onerous computational terms. Artificial intelligence can be solution this sense. In particular, research delves into application Generative Adversarial Networks (GAN) for dual-channel complex FP image enhancement human kidney samples. The study underscores GANs' efficacy promoting biological architectures domain, thereby still guaranteeing high resolution visibility detailed microscopic structures. We demonstrate successful GAN-based enhanced reconstruction through two strategies: cross-explainability expert survey. evaluated comparison explanation maps both real imaginary components underlining its robustness. This further shows that their interplay pivotal accurate without hallucinations. Secondly, accuracy effectiveness workflow are confirmed two-step survey conducted nephrologists.

Language: Английский

---

Plug-and-play DPC-based quantitative phase microscope

Biomedical Optics Express, Journal Year: 2024, Volume and Issue: 15(3), P. 1785 - 1785

Published: Feb. 7, 2024

Point-of-care testing (POCT) plays an increasingly important role in biomedical research and health care. Quantitative phase microscopes (QPMs) with good contrast, no invasion, labeling, high speed automation could be effectively applied for POCT. However, most QPMs are fixed on the optical platform bulky size, lack of timeliness, which remained challenging POCT solutions. In this paper, we proposed a plug-and-play QPM multimode imaging based quantitative differential contrast (qDPC) method. The system employs programmable LED array as light source uses GPU to accelerate calculation, can realize multi-contrast six modes. Accurate measurement real-time implemented by qDPC algorithms targets samples. A 3D electric control is designed mechanical field view focusing without manual operations. experimental results verify robustness performance setup. Even rookie finish scheme applications at scene using compact size 140 × 165 250 mm 3 .

Language: Английский

---

Recent Advances and Current Trends in Transmission Tomographic Diffraction Microscopy

Sensors, Journal Year: 2024, Volume and Issue: 24(5), P. 1594 - 1594

Published: Feb. 29, 2024

Optical microscopy techniques are among the most used methods in biomedical sample characterization. In their more advanced realization, optical microscopes demonstrate resolution down to nanometric scale. These rely on use of fluorescent labeling order break diffraction limit. However, molecules’ phototoxicity or photobleaching is not always compatible with investigated samples. To overcome this limitation, quantitative phase imaging have been proposed. Among these, holographic has demonstrated its ability image living microscopic samples without staining. for a 3D assessment samples, tomographic acquisitions needed. Tomographic Diffraction Microscopy (TDM) combines reconstructions. Relying synthetic aperture process, TDM allows measurements complex refractive index sample. Since initial proposition by Emil Wolf 1969, concept found lot applications and become one hot topics imaging. This review focuses recent achievements development. Current trends perspectives technique also discussed.

Language: Английский

---