AIMC Topic: Interferometry

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Ensemble machine learning prediction model for clinical refraction using partial interferometry measurements in childhood.

PloS one Jul 10, 2025
PURPOSE: To develop an ensemble machine learning prediction model for clinical refraction in childhood using partial interferometry measurements.
Myopia Refractive Errors Humans Male Refraction, Ocular Machine Learning Child Retrospective Studies Interferometry Female Adolescent Child, Preschool
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C-reactive protein (CRP) evaluation in human urine using optical sensor supported by machine learning.

Scientific reports Aug 14, 2024
The rapid and sensitive indicator of inflammation in the human body is C-Reactive Protein (CRP). Determination of CRP level is important in medical diagnostics because, depending on that factor, it may indicate, e.g., the occurrence of inflammation o...
C-Reactive Protein Urinary Tract Infections Optical Fibers Interferometry Biosensing Techniques Inflammation Machine Learning Sepsis Humans
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Beyond Correlations: Deep Learning for Seismic Interferometry.

IEEE transactions on neural networks and learning systems Jul 6, 2023
Passive seismic interferometry is a vastly generalized blind deconvolution question, where different paths through the Earth correspond to different channels called Green's functions; the sources are completely incoherent and not shared by the channe...
Noise Acoustics Interferometry Neural Networks, Computer Deep Learning
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Machine learning assisted interferometric structured illumination microscopy for dynamic biological imaging.

Nature communications Dec 21, 2022
Structured Illumination Microscopy, SIM, is one of the most powerful optical imaging methods available to visualize biological environments at subcellular resolution. Its limitations stem from a difficulty of imaging in multiple color channels at onc...
Lighting Machine Learning Interferometry Microscopy, Fluorescence
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Fringe Detection and Displacement Sensing for Variable Optical Feedback-Based Self-Mixing Interferometry by Using Deep Neural Networks.

Sensors (Basel, Switzerland) Dec 14, 2022
Laser feedback-based self-mixing interferometry (SMI) is a promising technique for displacement sensing. However, commercial deployment of such sensors is being held back due to reduced performance in case of variable optical feedback which invariabl...
Lasers, Semiconductor Feedback Interferometry Equipment Design Neural Networks, Computer
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High-resolution single-shot phase-shifting interference microscopy using deep neural network for quantitative phase imaging of biological samples.

Journal of biophotonics May 7, 2021
White light phase-shifting interference microscopy (WL-PSIM) is a prominent technique for high-resolution quantitative phase imaging (QPI) of industrial and biological specimens. However, multiple interferograms with accurate phase-shifts are essenti...
Microscopy, Interference Interferometry Humans Neural Networks, Computer Light
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Beetle-inspired responsive photonic microgel assemblies for multi-sensing enhanced by machine learning.

Biosensors & bioelectronics Oct 15, 2025
Bioinspired photonic hydrogels hold promise as sensors; however, their use in triple-analyte sensing optical devices has been minimally explored. Temperature, serum Fe levels, and X-ray doses are critical factors for predicting and monitoring medical...
Machine Learning Temperature Humans Neural Networks, Computer Iron Ferrous Compounds Animals Biosensing Techniques Photons Interferometry Hydrogels Metallocenes
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Single-shot multispectral quantitative phase imaging of biological samples using deep learning.

Applied optics May 20, 2023
Multispectral quantitative phase imaging (MS-QPI) is a high-contrast label-free technique for morphological imaging of the specimens. The aim of the present study is to extract spectral dependent quantitative information in single-shot using a highly...
Neural Networks, Computer Holography Deep Learning Interferometry
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Application of attention-DnCNN for ESPI fringe patterns denoising.

Journal of the Optical Society of America. A, Optics, image science, and vision Nov 1, 2022
Fringe patterns' denoising in electronic speckle pattern interferometry (ESPI) is an important step in phase extraction. In this study, we propose a new denoising method for ESPI fringe patterns based on a convolutional neural network (CNN). The prop...
Neural Networks, Computer Electronics Interferometry
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Dual-wavelength interferogram decoupling method for three-frame generalized dual-wavelength phase-shifting interferometry based on deep learning.

Journal of the Optical Society of America. A, Optics, image science, and vision Mar 1, 2021
In dual-wavelength interferometry, the key issue is how to efficiently retrieve the phases at each wavelength using the minimum number of wavelength-multiplexed interferograms. To address this problem, a new dual-wavelength interferogram decoupling m...
Interferometry Deep Learning Humans Erythrocytes Algorithms
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