On the use of deep learning for phase recovery

Light Science & Applications, Год журнала: 2024, Номер 13(1)

Опубликована: Янв. 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

Язык: Английский

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Intelligent polarization-sensitive holographic flow-cytometer: Towards specificity in classifying natural and microplastic fibers

The Science of The Total Environment, Год журнала: 2022, Номер 815, С. 152708 - 152708

Опубликована: Янв. 3, 2022

Язык: Английский

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A Critical Review on Artificial Intelligence—Based Microplastics Imaging Technology: Recent Advances, Hot-Spots and Challenges

International Journal of Environmental Research and Public Health, Год журнала: 2023, Номер 20(2), С. 1150 - 1150

Опубликована: Янв. 9, 2023

Due to the rapid artificial intelligence technology progress and innovation in various fields, this research aims use science mapping tools comprehensively objectively analyze recent advances, hot-spots, challenges intelligence-based microplastic-imaging field from Web of Science (2019–2022). By text mining visualization scientific literature we emphasized some opportunities bring forward further explication analysis by (i) exploring efficient low-cost automatic quantification methods appearance properties microplastics, such as shape, size, volume, topology, (ii) investigating microplastics water-soluble synthetic polymers interaction with other soil water ecology environments via technologies, (iii) advancing algorithms models, even including intelligent robot technology, (iv) seeking create share robust data sets, spectral libraries toxicity database co-operation mechanism, (v) optimizing existing deep learning models based on readily available set balance related algorithm performance interpretability, (vi) facilitating Unmanned Aerial Vehicle coupled technologies sets mass quantities microplastics. Our major findings were that revolutionize environmental was progressing toward multiple cross-cutting areas, dramatically increasing aspects plastisphere, toxicity, identification, volume assessment The above can not only determine characteristics track development, but also help find suitable carry out more in-depth many problems remaining.

Язык: Английский

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Recent trends in marine microplastic modeling and machine learning tools: Potential for long-term microplastic monitoring

Journal of Applied Physics, Год журнала: 2023, Номер 133(2)

Опубликована: Янв. 11, 2023

The increase in the global demand for plastics, and more recently during pandemic, is a major concern future of plastic waste pollution microplastics. Efficient microplastic monitoring imperative to understanding long-term effects progression environment. Numerical models are valuable studying transport as they can be used examine different parameters systematically help elucidate fate processes microplastics, thus providing holistic view microplastics ocean By incorporating physical (such size, shape, density, identity microplastics), numerical have gained better physics transport, predicted sinking velocities accurately, estimated pathways marine environments. However, availability large amounts information about chemical sparse. Machine learning computer-vision tools aid acquiring environmental provide input develop accurate verify their predictions. More further facilitate efforts, optimize where data collection take place ultimately improve machine tools. This review offers perspective on how image-based exploited uncover behaviors. Additionally, authors hope inspires studies that bridge gap between modeling analysis exploit joined potential.

Язык: Английский

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Smart polarization and spectroscopic holography for real-time microplastics identification

Communications Engineering, Год журнала: 2024, Номер 3(1)

Опубликована: Фев. 17, 2024

Abstract Optical microscopy technologies as prominent imaging methods can offer rapid, non-destructive, non-invasive detection, quantification, and characterization of tiny particles. However, optical systems generally incorporate spectroscopy chromatography for precise material determination, which are usually time-consuming labor-intensive. Here, we design a polarization spectroscopic holography to automatically analyze the molecular structure composition, namely smart (SPLASH). This approach improves evaluation performance by integrating multi-dimensional features, thereby enabling highly accurate efficient identification. It simultaneously captures states-related, holographic, texture features spectroscopy, without physical implementation system. By leveraging Stokes mask (SPM), SPLASH achieves simultaneous four states. Its effectiveness has been demonstrated in application microplastics (MP) With machine learning methods, such ensemble subspace discriminant classifier, k-nearest neighbors support vector machine, depicts MPs with anisotropy, interference fringes, refractive index, morphological characteristics performs explicit discrimination over 0.8 value area under curve less than 0.05 variance. technique is promising tool addressing increasing public concerning issues MP pollution assessment, source identification, long-term water monitoring.

Язык: Английский

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In-situ detection of microplastics in the aquatic environment: A systematic literature review

The Science of The Total Environment, Год журнала: 2024, Номер 934, С. 173111 - 173111

Опубликована: Май 12, 2024

Microplastics are ubiquitous in the aquatic environment and have emerged as a significant environmental issue due to their potential impacts on human health ecosystem. Current laboratory-based microplastic detection methods suffer from various drawbacks, including lack of standardisation, limited spatial temporal coverage, high costs, time-consuming procedures. Consequently, there is need for development in-situ techniques detect monitor microplastics effectively identify understand sources, pathways, behaviours. Herein, we adopt systematic literature review method assess application experimental field technologies designed monitoring microplastics, without sample preparation. Four scientific databases were searched March 2023, resulting 62 relevant studies. These studies classified into seven sensor categories working principles discussed. The classes include optical devices, digital holography, Raman spectroscopy, other hyperspectral imaging, remote sensing, methods. We also looked at how data these integrated with machine learning models develop classifiers capable accurately characterising physical chemical properties discriminating them particles. This concluded that environments feasible can be achieved accuracy, even though still early stages development. Nonetheless, further research needed enhance microplastics. includes exploring possibility combining developing robust machine-learning classifiers. Additionally, recommendation implementation reviewed effectiveness detecting limitations.

Язык: Английский

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Flow Cytometry as a Rapid Alternative to Quantify Small Microplastics in Environmental Water Samples

Water, Год журнала: 2022, Номер 14(9), С. 1436 - 1436

Опубликована: Апрель 30, 2022

The most frequently used method to quantify microplastics (MPs) visually by microscope is time consuming and labour intensive, where the also hindered size limitation at 10 µm or even higher. A proposed perform pre-concentration of MPs vacuum filtration, hydrogen peroxide wet digestion, fluorescent staining flow cytometric determination rapidly detect small sized from 1–50 µm. performance was evaluated spiking seven different types polymer, including polystyrene (PS), low-density polyethylene (LDPE), polypropylene (PP), poly(methyl methacrylate) (PMMA), polyvinyl chloride (PVC), polylactic acid (PLA) acrylonitrile butadiene styrene (ABS) levels (400, 4000, 40,000 particles mL−1), with a satisfactory overall % recoveries (101 ± 19.4%) observed, in general no significant difference between two methods observed. Furthermore, process filtration introduced reduce matrix effect. After pre-concentration, accuracy MP counts resulted both ultrapure water (94.33 11.16%) sea (103.17 9.50%) samples. validated using cytometry can be environmental samples that human resources.

Язык: Английский

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Snapshot Polarization-Sensitive Holography for Detecting Microplastics in Turbid Water

ACS Photonics, Год журнала: 2023, Номер 10(12), С. 4483 - 4493

Опубликована: Ноя. 30, 2023

Microplastic (MP) pollution is a serious environmental problem, which can severely harm the earth's ecosystems and human health. However, in situ characterization of MP particles remains challenging due to complex natural environments such as turbid water. In this work, hybrid computational imaging approach based on holography polarimetry developed for rapid accurate assessment particular, influence scattering media detection experimentally studied. With compact optical configuration an efficient method, system capable seeing through obtaining multimodal information about object snapshot. The results suggest that polarization features substantially improve image contrast even highly addition, it demonstrated properties objects are new discriminative identifying materials. Therefore, portable extremely useful further development monitoring environments.

Язык: Английский

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Advanced Optical Imaging Technologies for Microplastics Identification: Progress and Challenges

Advanced Photonics Research, Год журнала: 2024, Номер 5(11)

Опубликована: Июль 22, 2024

Global concern about microplastic (MP) and nanoplastic (NP) particles is continuously rising with their proliferation worldwide. Effective identification methods for MP NP pollution monitoring are highly needed, but due to different requirements technical challenges, much of the work still in progress. Herein, advanced optical imaging systems that successfully applied or have potential focused on. Compared chemical thermal analyses, unique advantages being nondestructive noncontact allow fast detection without complex sample preprocessing. Furthermore, they capable revealing morphology, anisotropy, material characteristics quick robust detection. This review aims present a comprehensive discussion relevant systems, emphasizing operating principles, strengths, drawbacks. Multiple comparisons analyses among these technologies conducted order provide practical guidelines researchers. In addition, combination other alternative described representative portable devices highlighted. Together, shed light on prospects long‐term environmental protection.

Язык: Английский

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Recognition and detection technology for microplastic, its source and health effects

Environmental Science and Pollution Research, Год журнала: 2024, Номер 31(8), С. 11428 - 11452

Опубликована: Янв. 6, 2024

Язык: Английский

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