Deep learning in optical metrology: a review

Light Science & Applications, Journal Year: 2022, Volume and Issue: 11(1)

Published: Feb. 23, 2022

Abstract With the advances in scientific foundations and technological implementations, optical metrology has become versatile problem-solving backbones manufacturing, fundamental research, engineering applications, such as quality control, nondestructive testing, experimental mechanics, biomedicine. In recent years, deep learning, a subfield of machine is emerging powerful tool to address problems by learning from data, largely driven availability massive datasets, enhanced computational power, fast data storage, novel training algorithms for neural network. It currently promoting increased interests gaining extensive attention its utilization field metrology. Unlike traditional “physics-based” approach, deep-learning-enabled kind “data-driven” which already provided numerous alternative solutions many challenging this with better performances. review, we present an overview current status latest progress deep-learning technologies We first briefly introduce both image-processing basic concepts followed comprehensive review applications various tasks, fringe denoising, phase retrieval, unwrapping, subset correlation, error compensation. The open challenges faced approach are then discussed. Finally, directions future research outlined.

Language: Английский

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Nano Biosensors: Properties, applications and electrochemical techniques

Journal of Materials Research and Technology, Journal Year: 2021, Volume and Issue: 12, P. 1649 - 1672

Published: March 27, 2021

A sensor is a tool used to directly measure the test compound (analyte) in sample. Ideally, such device capable of continuous and reversible response should not damage Nanosensor refers system which at least one nanostructures detect gases, chemicals, biological agents, electric fields, light, heat, etc. its construction. The use nanomaterials significantly increases sensitivity system. In biosensors, part attach analyte specifically it element (such as DNA strand, antibody, enzyme, whole cell). "Nano Biosensors" series reviews various types biosensors biochips (including an array biosensors), emphasizing role nanostructures, developed for medical applications. Nano Biosensors Electrochemical sensors are that diagnostic component electrode transducer. these systems usually done fill gap between converter bioreceptor, nanoscale. Given nature biomaterial detection process, electrochemical divided into catalytic propulsion. Common techniques common include potentiometric, chronometry, voltammetry, impedance measurement, field effect transistor (FET). Simultaneous advantages has led emergence with high decomposition power. Various including nanoparticles, nanotubes nanowires, nanopores, self-adhesive monolayers nanocomposites can be improve performance efficiency their structure.

Language: Английский

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Orthogonal learning covariance matrix for defects of grey wolf optimizer: Insights, balance, diversity, and feature selection

Knowledge-Based Systems, Journal Year: 2020, Volume and Issue: 213, P. 106684 - 106684

Published: Dec. 17, 2020

Language: Английский

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Quantitative Phase Imaging: Recent Advances and Expanding Potential in Biomedicine

ACS Nano, Journal Year: 2022, Volume and Issue: 16(8), P. 11516 - 11544

Published: Aug. 2, 2022

Quantitative phase imaging (QPI) is a label-free, wide-field microscopy approach with significant opportunities for biomedical applications. QPI uses the natural shift of light as it passes through transparent object, such mammalian cell, to quantify biomass distribution and spatial temporal changes in biomass. Reported cell studies more than 60 years ago, ongoing advances hardware software are leading numerous applications biology, dramatic expansion utility over past two decades. Today, investigations size, morphology, behavior, cellular viscoelasticity, drug efficacy, accumulation turnover, transport mechanics supporting development, physiology, neural activity, cancer, additional physiological processes diseases. Here, we review field biology starting underlying principles, followed by discussion technical approaches currently available or being developed, end an examination breadth use under development. We comment on strengths shortcomings deployment key contexts conclude emerging challenges based combining other methodologies that expand scope even further.

Language: Английский

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Dual-plane coupled phase retrieval for non-prior holographic imaging

PhotoniX, Journal Year: 2022, Volume and Issue: 3(1)

Published: Jan. 28, 2022

Abstract Accurate depiction of waves in temporal and spatial is essential to the investigation interactions between physical objects waves. Digital holography (DH) can perform quantitative analysis wave–matter interactions. Full detector-bandwidth reconstruction be realized based on in-line DH. But overlapping twin images strongly prevents analysis. For off-axis DH, object wave detector bandwidth need satisfy certain conditions accurately. Here, we present a reliable approach involving coupled configuration for combining two holograms one hologram, using rapidly converging iterative procedure two-plane phase retrieval (TwPCPR) method. It realizes fast-convergence holographic calculation High-resolution full-field by exploiting full are demonstrated complex-amplitude reconstruction. Off-axis optimization provides an effective initial guess avoid stagnation minimize required measurements multi-plane retrieval. The proposed strategy works well more extended samples without any prior assumptions including support, non-negative, sparse constraints, etc. helps enhance empower applications wavefront sensing, computational microscopy biological tissue

Language: Английский

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On the use of deep learning for phase recovery

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

Published: Jan. 1, 2024

Phase recovery (PR) refers to calculating the phase of light field from its intensity measurements. As exemplified quantitative imaging and coherent diffraction adaptive optics, PR is essential for reconstructing refractive index distribution or topography an object correcting aberration system. In recent years, deep learning (DL), often implemented through neural networks, has provided unprecedented support computational imaging, leading more efficient solutions various problems. this review, we first briefly introduce conventional methods PR. Then, review how DL provides following three stages, namely, pre-processing, in-processing, post-processing. We also used in image processing. Finally, summarize work provide outlook on better use improve reliability efficiency Furthermore, present a live-updating resource ( https://github.com/kqwang/phase-recovery ) readers learn about

Language: Английский

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Artificial intelligence-enabled quantitative phase imaging methods for life sciences

Nature Methods, Journal Year: 2023, Volume and Issue: 20(11), P. 1645 - 1660

Published: Oct. 23, 2023

Language: Английский

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Iterative projection meets sparsity regularization: towards practical single-shot quantitative phase imaging with in-line holography

Deleted Journal, Journal Year: 2023, Volume and Issue: 4(1), P. 1 - 1

Published: Jan. 1, 2023

Holography provides access to the optical phase. The emerging compressive phase retrieval approach can achieve in-line holographic imaging beyond information-theoretic limit or even from a single shot by exploring signal priors. However, iterative projection methods based on physical knowledge of wavefield suffer poor quality, whereas regularization techniques sacrifice robustness for fidelity. In this work, we present unified framework holography that encapsulates unique advantages both constraints and sparsity particular, constrained complex total variation (CCTV) regularizer is introduced explores well-known absorption support together with in gradient domain, enabling practical high-quality intensity image. We developed efficient solvers proximal method non-smooth regularized inverse problem corresponding denoising subproblem. Theoretical analyses further guarantee convergence algorithms prespecified parameters, obviating need manual parameter tuning. As simulated experiments demonstrate, proposed CCTV model characterize natural scenes while utilizing physically tractable quality enhancement. This new be extended, minor adjustments, various configurations, sparsifying operators, knowledge. It may cast light theoretical empirical studies.

Language: Английский

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Roadmap on Label‐Free Super‐Resolution Imaging

Laser & Photonics Review, Journal Year: 2023, Volume and Issue: 17(12)

Published: Oct. 30, 2023

Abstract Label‐free super‐resolution (LFSR) imaging relies on light‐scattering processes in nanoscale objects without a need for fluorescent (FL) staining required super‐resolved FL microscopy. The objectives of this Roadmap are to present comprehensive vision the developments, state‐of‐the‐art field, and discuss resolution boundaries hurdles that be overcome break classical diffraction limit label‐free imaging. scope spans from advanced interference detection techniques, where diffraction‐limited lateral is combined with unsurpassed axial temporal resolution, techniques true capability based understanding as an information science problem, using novel structured illumination, near‐field scanning, nonlinear optics approaches, designing superlenses nanoplasmonics, metamaterials, transformation optics, microsphere‐assisted approaches. To end, brings under same umbrella researchers physics biomedical communities which such studies have often been developing separately. ultimate intent paper create current future developments LFSR its physical mechanisms great opening series articles field.

Language: Английский

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Quantitative phase imaging based on holography: trends and new perspectives

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

Published: June 27, 2024

Abstract In 1948, Dennis Gabor proposed the concept of holography, providing a pioneering solution to quantitative description optical wavefront. After 75 years development, holographic imaging has become powerful tool for wavefront measurement and phase imaging. The emergence this technology given fresh energy physics, biology, materials science. Digital holography (DH) possesses advantages wide-field, non-contact, precise, dynamic capability complex-waves. DH unique capabilities propagation fields by measuring light scattering with information. It offers visualization refractive index thickness distribution weak absorption samples, which plays vital role in pathophysiology various diseases characterization materials. provides possibility bridge gap between disciplines. is described complex amplitude. complex-value complex-domain reconstructed from intensity-value camera real-domain. Here, we regard process recording reconstruction as transformation real-domain, discuss mathematics physical principles reconstruction. We review underlying principles, technical approaches, breadth applications. conclude emerging challenges opportunities based on combining other methodologies that expand scope utility even further. multidisciplinary nature brings application experts together label-free cell analytical chemistry, clinical sciences, sensing, semiconductor production.

Language: Английский

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