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44-4: MicroLED Arrays as Light Source for Optical Sectioning-SIM and Targeted Illumination Imaging

SID Symposium Digest of Technical Papers 2024年第1期55卷 588-591页

作者： Vikrant Kumar Catherine A. Saladrigas Oliver Durnan Forest Speed Victor M. Bright Diego Restrepo Emily A. Gibson Juliet T. Gopinath Ioannis Kymissis Department of Electrical Engineering Columbia University New York USA Department of Electrical Computer and Energy Engineering University of Colorado Boulder USA Department of Bioengineering University of Colorado Anschutz Medical Campus Aurora USA Department of Mechanical Engineering University of Colorado Boulder USA Department of Physics University of Colorado Boulder USA

This work discusses microLED arrays as light sources for implementing optical sectioning structured illumination microscopy (OS-SIM) and targeted illumination (TI) for neural imaging applications. We demonstrated a microstripe array to generate patterned light for OS-SIM and an individually addressable 20 × 20 microLED array as a light source for implementing TI in a widefield imaging setup.

关键词： MicroLED Arrays Neural Imaging Light Source Optical Sectioning Targeted Illumination

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SPECTRALLY-ENCODED NON-SCANNING IMAGING THROUGH A FIBER

arXiv

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arXiv 2023年

作者： Xie, Ningzhi Tanguy, Quentin A.A. Fröch, Johannes E. Böhringer, Karl F. Majumdar, Arka Department of Electrical and Computer Engineering University of Washington SeattleWA98195 United States Department of Electrical and Computer Engineering Department of Physics University of Washington SeattleWA98195 United States Department of Electrical and Computer Engineering Department of Bioengineering University of Washington SeattleWA98195 United States

With the advent of neuroimaging and microsurgery, there is a rising need for capturing images through an optical fiber. We present an approach of imaging through a single fiber without mechanical scanning by implementing spatial-spectral encoding. The spectral encoding is achieved through a microfabricated spectral filter array, where light from different spatial pixels is coded with a highly orthogonal spectrum. The image is then computationally recovered via pseudo inverse of the encoding process. We demonstrate imaging of a 4 × 4 binary object at the proximity of the spectral filter array using 560 − 625nm wavelength band. The recovered image maintains an error rate of © 2023, CC BY-NC-ND.

关键词： Encoding (symbols)

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Single-shot quantitative phase gradient microscopy using physics-based untrained neural network phase retrieval 11

Single-shot quantitative phase gradient microscopy using phy...

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Quantitative Phase Imaging XI 2025

作者： Hur, Sun Woong Sengupta, Sourya Kwon, Minsung Manoharaan, Revathi Anastasio, Mark Bhargava, Rohit Department of Bioengineering University of Illinois Urbana-ChampaignIL United States Department of Electrical and Computer Engineering University of Illinois Urbana-ChampaignIL United States Beckman Institute for Advanced Science and Technology University of Illinois Urbana-ChampaignIL United States Department of Computer Science Carle-Illinois College of Medicine University of Illinois Urbana-ChampaignIL United States Department of Chemical and Biomolecular Engineering Mechanical Science and Engineering and Chemistry Cancer Center at Illinois University of Illinois Urbana-ChampaignIL United States CZ Biohub Chicago LLC IL United States

ISBN: (纸本)9781510684065

Single-shot quantitative phase gradient microscopy (ss-QPGM) enables quantitative phase imaging (QPI) based on differential interference contrast (DIC) microscopy. In ss-QPGM, the analyzer is replaced by a quarter-wave plate and a polarization camera, allowing for phase gradient extraction from a single intensity measurement. The quantitative phase image is reconstructed via numerical integration, but direct integration along a single axis introduces artifacts and phase errors due to missing frequency response along the axis of orthogonal to the shear axis and noise-induced streak lines. In this work, we propose a phase retrieval method for ss-QPGM using an untrained neural network (UNN), which integrates physical priors without requiring paired ground truth and input datasets, overcoming the limitations of traditional regularization methods such as Tikhonov regularization and the alternating direction method of multipliers (ADMM) with total variation (TV) regularization. We demonstrate that the UNN approach not only offers superior phase reconstruction but also alleviates artifacts induced by missing frequency response along the axis and noise-induced streak lines, as shown by phase images of a calibrated target and biological samples. © 2025 SPIE.

关键词： Image reconstruction

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Two-Stage Hierarchical and Explainable Feature Selection Framework for Dimensionality Reduction in Sleep Staging

arXiv

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arXiv 2024年

作者： Deng, Yangfan Albidah, Hamad Dallal, Ahmed Yin, Jijun Mao, Zhi-Hong The Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA15261 United States The Department of Bioengineering University of Pittsburgh PittsburghPA15261 United States

Sleep is crucial for human health, and EEG signals play a significant role in sleep research. Due to the high-dimensional nature of EEG signal data sequences, data visualization and clustering of different sleep stages have been challenges. To address these issues, we propose a two-stage hierarchical and explainable feature selection framework by incorporating a feature selection algorithm to improve the performance of dimensionality reduction. Inspired by topological data analysis, which can analyze the structure of high-dimensional data, we extract topological features from the EEG signals to compensate for the structural information loss that happens in traditional spectro-temporal data analysis. Supported by the topological visualization of the data from different sleep stages and the classification results, the proposed features are proven to be effective supplements to traditional features. Finally, we compare the performances of three dimensionality reduction algorithms: Principal Component Analysis (PCA), t-Distributed Stochastic Neighbor Embedding (t-SNE), and Uniform Manifold Approximation and Projection (UMAP). Among them, t-SNE achieved the highest accuracy of 79.8%, but considering the overall performance in terms of computational resources and metrics, UMAP is the optimal choice. Copyright © 2024, The Authors. All rights reserved.

关键词： Dimensionality reduction

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Retinal Vascular System Segmentation based on Non-Linear Map-Based Estimation of Joint MGRF Model

Retinal Vascular System Segmentation based on Non-Linear Map...

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IEEE International Symposium on Biomedical Imaging

作者： Ahmed Alksas Ahmed Sharafeldeen Hossam Magdy Balaha Mohamed Ghazal Marah Alhalabi Ali Mahmoud Rasha Hassan Jawad Yousaf Harpal Sandhu Ayman El-Baz Department of Bioengineering University of Louisville Louisville KY USA Electrical Computer and Biomedical Engineering Department Abu Dhabi University Abu Dhabi United Arab Emirates

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

We introduce a novel, fully automated, unsupervised segmentation technique for extracting the vascular system from retinal Optical Coherence Tomography Angiography (OCTA) images, a crucial component in computer-aided diagnostic systems for retinal disease detection. Our approach integrates a two-level joint Markov-Gibbs Random Field (MGRF) framework, featuring a new probabilistic model—the Linear Combination of Discrete Gaussian (LCDG). The first level addresses OCTA image appearance and their spatially smoothed counterparts through LCDG, with parameters refined by an enhanced Expectation Maximization (EM) algorithm. The second level captures vascular and retinal tissue maps via MGRF, utilizing parameters analytically derived from images. A novel application of modified self-organizing maps, acting as a MAP-based optimizer, enables unsupervised, nonlinear optimization-driven segmentation, marking a departure from traditional methods. Evaluated on a dataset of 204 subjects, our framework achieves significant metrics: a Dice similarity coefficient of 0.90±0.04, a 95-percentile bidirectional Hausdorff distance of 0.79 ± 0.28, and an accuracy of 0.86 ± 0.06, underscoring its effectiveness.

关键词： Self-organizing feature maps Measurement Image segmentation Optical coherence tomography Computational modeling Biological system modeling Estimation

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Multiplane quantitative phase imaging using a wavelength-multiplexed diffractive optical processor

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Advanced Photonics 2024年第5期6卷 51-69页

作者： Che-Yung Shen Jingxi Li Yuhang Li Tianyi Gan Langxing Bai Mona Jarrahi Aydogan Ozcan University of California Los AngelesElectrical and Computer Engineering DepartmentLos AngelesCaliforniaUnited States University of California Los AngelesBioengineering DepartmentLos AngelesCaliforniaUnited States University of California Los AngelesCalifornia NanoSystems InstituteLos AngelesCaliforniaUnited States University of California Los AngelesDepartment of Computer ScienceLos AngelesCaliforniaUnited States

Quantitative phase imaging(QPI)is a label-free technique that provides optical path length information for transparent specimens,finding utility in biology,materials science,and ***,we present QPI of a three-dimensional(3D)stack of phase-only objects using a wavelength-multiplexed diffractive optical *** multiple spatially engineered diffractive layers trained through deep learning,this diffractive processor can transform the phase distributions of multiple two-dimensional objects at various axial positions into intensity patterns,each encoded at a unique wavelength *** wavelength-multiplexed patterns are projected onto a single field of view at the output plane of the diffractive processor,enabling the capture of quantitative phase distributions of input objects located at different axial planes using an intensity-only image *** on numerical simulations,we show that our diffractive processor could simultaneously achieve all-optical QPI across several distinct axial planes at the input by scanning the illumination wavelength.A proof-of-concept experiment with a 3D-fabricated diffractive processor further validates our approach,showcasing successful imaging of two distinct phase objects at different axial positions by scanning the illumination wavelength in the terahertz *** network-based multiplane QPI designs can open up new avenues for compact on-chip phase imaging and sensing devices.

关键词： quantitative phase imaging three-dimensional imaging label-free imaging diffractive neural networks computational imaging

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All-optical synthesis of an arbitrary linear transformation using diffractive surfaces

引用

Light(Science & Applications) 2021年第10期10卷 1928-1948页

作者： Onur Kulce Deniz Mengu Yair Rivenson Aydogan Ozcan Electrical and Computer Engineering Department University of CaliforniaLos AngelesCA 90095USA Bioengineering Department University of CaliforniaLos AngelesCA 90095USA California NanoSystems Institute University of CaliforniaLos AngelesCA 90095USA

Spatially-engineered diffractive surfaces have emerged as a powerful framework to control light-matter interactions for statistical inference and the design of task-specific optical ***,we report the design of diffractive surfaces to all-optically perform arbitrary complex-valued linear transformations between an input(Ni)and output(No),where Ni and No represent the number of pixels at the input and output fields-of-view(FOVs),***,we consider a single diffractive surface and use a matrix pseudoinverse-based method to determine the complex-valued transmission coefficients of the diffractive features/neurons to all-optically perform a desired/target linear *** addition to this data-free design approach,we also consider a deep learning-based design method to optimize the transmission coefficients of diffractive surfaces by using examples of input/output fields corresponding to the target *** compared the all-optical transformation errors and diffraction efficiencies achieved using data-free designs as well as data-driven(deep learning-based)diffractive designs to all-optically perform(i)arbitrarily-chosen complex-valued transformations including unitary,nonunitary,and noninvertible transforms,(ii)2D discrete Fourier transformation,(iii)arbitrary 2D permutation operations,and(iv)high-pass filtered coherent *** analyses reveal that if the total number(N)of spatially-engineered diffractive features/neurons is≥Ni×No,both design methods succeed in all-optical implementation of the target transformation,achieving negligible ***,compared to data-free designs,deep learning-based diffractive designs are found to achieve significantly larger diffraction efficiencies for a given N and their all-optical transformations are more accurate for N

关键词： arbitrary valued unitary

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Regularizing Numerical Extremals Along Singular Arcs: A Lie-Theoretic Approach

arXiv

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arXiv 2024年

作者： de Oliveira, Arthur Castello Branco Siami, Milad Sontag, Eduardo D. Department of Electrical and Computer Engineering Northeastern University BostonMA02115 United States Department of Bioengineering Northeastern University BostonMA02115 United States

Numerical "direct" approaches to time-optimal control often fail to find solutions that are singular in the sense of the Pontryagin Maximum Principle, performing better when searching for saturated (bang-bang) solutions. In previous work by one of the authors, singular solutions were shown to exist for the time-optimal control problem for fully actuated mechanical systems under hard torque constraints. Explicit formulas, based on a Lie theoretic analysis of the problem, were given for singular segments of trajectories, but the global structure of solutions remains unknown. In this work, we review the aforementioned framework, and show how to effectively combine these formulas with the use of general-purpose optimal control software packages. By using the explicit formula given by the theory in the intervals where the numerical solution enters a singular arc, we not only obtain an algebraic expression for the control in that interval but we are also able to remove artifacts present in the numerical solution. In this way, the best features of numerical algorithms and theory complement each other and provide a better picture of the global optimal structure. We illustrate the technique on a two degree of freedom robotic arm example, using two distinct optimal control numerical software packages running on different programming languages. © 2024, CC BY-NC-SA.

关键词： Software packages

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All-optical information-processing capacity of diffractive surfaces

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Light(Science & Applications) 2021年第2期10卷 217-233页

The precise engineering of materials and surfaces has been at the heart of some of the recent advances in optics and *** advances related to the engineering of materials with new functionalities have also opened up exciting avenues for designing trainable surfaces that can perform computation and machine-learning tasks through light-matter interactions and ***,we analyze the information-processing capacity of coherent optical networks formed by diffractive surfaces that are trained to perform an all-optical computational task between a given input and output *** show that the dimensionality of the all-optical solution space covering the complex-valued transformations between the input and output fields-of-view is linearly proportional to the number of diffractive surfaces within the optical network,up to a limit that is dictated by the extent of the input and output *** diffractive networks that are composed of larger numbers of trainable surfaces can cover a higher-dimensional subspace of the complex-valued linear transformations between a larger input field-of-view and a larger output field-of-view and exhibit depth advantages in terms of their statistical inference,learning,and generalization capabilities for different image classification tasks when compared with a single trainable diffractive *** analyses and conclusions are broadly applicable to various forms of diffractive surfaces,including,e.g.,plasmomc and/or dielectric-based metasurfaces and flat optics,which can be used to form all-optical processors.

关键词： surface. valued optics

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2p autofluorescence imaging endoscope for clinical observation of metabolic changes in cervical tissue 18

2p autofluorescence imaging endoscope for clinical observati...

引用

Endoscopic Microscopy XVIII 2023

作者： Camli, Berk Andrus, Liam P. Roy, Aditya Mishra, Biswajit Xu, Chris Georgakoudi, Irene Tkaczyk, Tomasz Ben-Yakar, Adela UT Austin Department of Mechanical Engineering AustinTX United States UT Austin Department of Biomedical Engineering AustinTX United States Cornell University School of Applied and Engineering Physics IthacaNY United States Tufts University Department of Biomedical Engineering MedfordMA United States Rice University Department of Bioengineering HoustonTX United States UT Austin Department of Electrical and Computer Engineering AustinTX United States

ISBN: (纸本)9781510658172

Imaging modalities capable of detecting functional changes over small areas can increase sensitivity and specificity of early cancer detection. Label-free imaging of metabolic activity at cellular level resolution over full thickness of cervix epithelium is possible with 2p imaging. However, low probability of 2p excitation and scattering nature of tissues limit autofluorescence levels in 2p imaging. We present a 2p autofluorescence imaging endoscope system for detection of metabolic changes in cervix in a clinical setting, with an increased collection efficiency in scattering media. Collection of autofluorescence signals is done with a multitude of high NA fibers arranged around a miniaturized excitation objective. By cleaving the collection fibers at a specific angle, we increase the directivity of the collection and the collection efficiency per fiber. The endoscope performs imaging at 775 nm, which is capable of exciting NAD(P)H and FAD molecules. Laser pulses of 100 fs duration are delivered to the sample with an air core photonic bandgap fiber. Fiber is scanned in spiral pattern via a piezo actuator tube. Scanning at different tissue depths is possible with the axial actuation of the endoscope via a linear stepper motor. Benchtop tests indicate that the endoscope system has lateral and axial resolutions of 0.65 µm and 4.33 µm, respectively. Fluorescence images of pollen cores are presented to demonstrate the imaging quality of the endoscope system. © 2023 SPIE.

关键词： Efficiency

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