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46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Huang, Jingya Tostado-Marcos, Pablo Narasimha, Sowmya Manojna Patel, Aashish N. Arneodo, Ezequiel. M. Gentner, Timothy Q. Mishne, Gal Gilja, Vikash University of California San Diego Department of Electrical and Computer Engineering La Jolla CA92092 United States University of California San Diego Department of Bioengineering La Jolla CA92092 United States University of California San Diego Institute for Neural Computation La Jolla CA92092 United States University of California San Diego Neuroscience Graduate Program La Jolla CA92092 United States University of California San Diego Department of Physics La Jolla CA92092 United States University of California San Diego Department of Psychology La Jolla CA92092 United States University of California San Diego Halicioǧlu Data Science Institute La Jolla CA92092 United States

ISBN: (纸本)9798350371499

State-of-the-art intracortical neuroprostheses currently enable communication at 60+ words per minute for anarthric individuals by training on over 10K sentences to account for phoneme variability in different word contexts. There is limited understanding about whether this performance can be maintained in decoding naturalistic speech with 40K+ word vocabularies across elicited, spontaneous, and conversational speech contexts. We introduce a vocal-unit-level generalization test to explicitly evaluate neural decoder performance with an expanded and more diverse behavioral repertoire. Tested on neural decoders modeling zebra finch vocalization, an analog to human vocal production, we compare three decoders with different input types: spike trains, neural factors, and firing rates. The factors and rates are latent neural features inferred using trained Latent Factor Analysis via Dynamical Systems (LFADS) models that capture the population neural dynamics during vocal production. While the conventional random holdout generalization error measure is similar for all three decoders, factor- and rate-based decoders outperform spike-based decoders when testing vocal-unit-holdout generalization error. These results suggest the later models better adapt to flexible vocalization inference when trained with partial observation of data variation, motivating further exploration of decoders incorporating latent neural and vocalization dynamics. © 2024 IEEE.

关键词： Errors

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Rapid Sensing of Hidden Objects and Defects using a Single-Pixel Diffractive Terahertz Processor

arXiv

引用

arXiv 2023年

作者： Li, Jingxi Li, Xurong Yardimci, Nezih T. Hu, Jingtian Li, Yuhang Chen, Junjie Hung, Yi-Chun Jarrahi, Mona Ozcan, Aydogan Electrical and Computer Engineering Department University of California Los AngelesCA90095 United States Bioengineering Department University of California Los AngelesCA90095 United States University of California Los AngelesCA90095 United States Physics & Astronomy Department University of California Los AngelesCA90095 United States

Terahertz waves offer numerous advantages for the nondestructive detection of hidden objects/defects in materials, as they can penetrate through most optically-opaque materials. However, existing terahertz inspection systems are restricted in their throughput and accuracy (especially for detecting small features) due to their limited speed and resolution. Furthermore, machine vision-based continuous sensing systems that use large-pixel-count imaging are generally bottlenecked due to their digital storage, data transmission and image processing requirements. Here, we report a diffractive processor that rapidly detects hidden defects/objects within a target sample using a single-pixel spectroscopic terahertz detector, without scanning the sample or forming/processing its image. This terahertz processor consists of passive diffractive layers that are optimized using deep learning to modify the spectrum of the terahertz radiation according to the absence/presence of hidden structures or defects. After its fabrication, the resulting diffractive processor all-optically probes the structural information of the sample volume and outputs a spectrum that directly indicates the presence or absence of hidden structures, not visible from outside. As a proof-of-concept, we trained a diffractive terahertz processor to sense hidden defects (including subwavelength features) inside test samples, and evaluated its performance by analyzing the detection sensitivity as a function of the size and position of the unknown defects. We validated its feasibility using a single-pixel terahertz time-domain spectroscopy setup and 3D-printed diffractive layers, successfully detecting hidden defects using pulsed terahertz illumination. This technique will be valuable for various applications, e.g., security screening, biomedical sensing, industrial quality control, anti-counterfeiting measures and cultural heritage protection. Copyright © 2023, The Authors. All rights reserved.

关键词： Defects

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Seeing through unknown, random diffusers using diffractive optical networks

Seeing through unknown, random diffusers using diffractive o...

引用

Conference on Lasers and Electro-Optics (CLEO)

作者： Yi Luo Yifan Zhao Jingxi Li Ege Çetintaş Yair Rivenson Mona Jarrahi Aydogan Ozcan Electrical and Computer Engineering Department University of California Los Angeles CA USA Bioengineering Department University of California Los Angeles CA USA California NanoSystems Institute (CNSI) University of California Los Angeles CA USA

Diffractive deep neural networks composed of spatially-engineered transmissive layers were designed and experimental demonstrated to see through unknown, random phase diffusers, instantaneously reconstructing images o... 详细信息

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

关键词： Digital computers Deep learning Neural networks Optical fiber networks Lasers and electrooptics Electrooptical waveguides Image reconstruction

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High-Dimensional MR Reconstruction Integrating Subspace and Adaptive Generative Models

arXiv

引用

arXiv 2023年

作者： Zhao, Ruiyang Peng, Xi Kelkar, Varun A. Anastasio, Mark A. Lam, Fan The Department of Electrical and Computer Engineering Beckman Institute for Advanced Science and Technology University of Illinois Urbana-Champaign IL61801 United States The Department of Radiology Mayo Clinic RochesterMN55902 United States The Department of Bioengineering Beckman Institute for Advanced Science and Technology University of Illinois Urbana-Champaign IL61801 United States

We present a novel method that integrates subspace modeling with an adaptive generative image prior for high-dimensional MR image reconstruction. The subspace model imposes an explicit low-dimensional representation of the high-dimensional images, while the generative image prior serves as a spatial constraint on the "contrast-weighted" images or the spatial coefficients of the subspace model. A formulation was introduced to synergize these two components with complimentary regularization such as joint sparsity. A special pretraining plus subject-specific network adaptation strategy was proposed to construct an accurate generative-model-based representation for images with varying contrasts, validated by experimental data. An iterative algorithm was introduced to jointly update the subspace coefficients and the multi-resolution latent space of the generative image model that leveraged a recently developed intermediate layer optimization technique for network inversion. We evaluated the utility of the proposed method in two high-dimensional imaging applications: accelerated MR parameter mapping and high-resolution MRSI. Improved performance over state-of-the-art subspace-based methods was demonstrated in both cases. Our work demonstrated the potential of integrating data-driven and adaptive generative models with low-dimensional representation for high-dimensional imaging problems. © 2023, CC BY.

关键词： Image reconstruction

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Diffractive Networks All-Optically Reconstruct Holograms

Diffractive Networks All-Optically Reconstruct Holograms

引用

Conference on Lasers and Electro-Optics (CLEO)

作者： Md Sadman Sakib Rahman Aydogan Ozcan Electrical and Computer Engineering Department University of California Los Angeles CA USA Bioengineering Department University of California Los Angeles CA USA California NanoSystems Institute (CNSI) University of California Los Angeles CA USA

We present a new framework for computer-free, all-optical reconstruction of inline holograms through a passive diffractive network that is trained with holographic image data using deep learning.

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

We present a new framework for computer-free, all-optical reconstruction of inline holograms through a passive diffractive network that is trained with holographic image data using deep learning.

关键词： Deep learning Lasers and electrooptics Electrooptical waveguides Image reconstruction

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To image, or not to image: Class-specific diffractive cameras with all-optical erasure of undesired objects

arXiv

引用

arXiv 2022年

作者： Bai, Bijie Luo, Yi Gan, Tianyi Hu, Jingtian Li, Yuhang Zhao, Yifan Mengu, Deniz Jarrahi, Mona Ozcan, Aydogan Electrical and Computer Engineering Department University of California Los AngelesCA90095 United States Bioengineering Department University of California Los Angeles90095 United States University of California Los AngelesCA United States

Privacy protection is a growing concern in the digital era, with machine vision techniques widely used throughout public and private settings. Existing methods address this growing problem by, e.g., encrypting camera images or obscuring/blurring the imaged information through digital algorithms. Here, we demonstrate a camera design that performs class-specific imaging of target objects with instantaneous all-optical erasure of other classes of objects. This diffractive camera consists of transmissive surfaces structured using deep learning to perform selective imaging of target classes of objects positioned at its input field-of-view. After their fabrication, the thin diffractive layers collectively perform optical mode filtering to accurately form images of the objects that belong to a target data class or group of classes, while instantaneously erasing objects of the other data classes at the output field-of-view. Using the same framework, we also demonstrate the design of class-specific permutation cameras, where the objects of a target data class are pixel-wise permuted for all-optical class-specific encryption, while the other objects are irreversibly erased from the output image. The success of class-specific diffractive cameras was experimentally demonstrated using terahertz (THz) waves and 3D-printed diffractive layers that selectively imaged only one class of the MNIST handwritten digit dataset, all-optically erasing the other handwritten digits. This diffractive camera design can be scaled to different parts of the electromagnetic spectrum, including, e.g., the visible and infrared wavelengths, to provide transformative opportunities for privacy-preserving digital cameras and task-specific data-efficient imaging. Copyright © 2022, The Authors. All rights reserved.

关键词： Terahertz waves

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MEMS-actuated metasurface Alvarez lens

引用

Microsystems & Nanoengineering 2020年第1期6卷 334-344页

作者： Zheyi Han Shane Colburn Arka Majumdar Karl F.Bohringer Department of Electrical and Computer Engineering University of WashingtonSeattleWashington 98195USA Institute for Nano-Engineered Systems University of WashingtonSeattleWashington 98195USA Department of Physics University of WashingtonSeattleWashington 98195USA Department of Bioengineering University of WashingtonSeattleWashington 98195USA

Miniature lenses with a tunable focus are essential components for many modern applications involving compact optical *** several tunable lenses have been reported with various tuning mechanisms,they often face challenges with respect to power consumption,tuning speed,fabrication cost,or production *** this work,we have adapted the mechanism of an Alvarez lens–a varifocal composite lens in which lateral shifts of two optical elements with cubic phase surfaces give rise to a change in the optical power–to construct a miniature,microelectromechanical system(MEMS)-actuated metasurface Alvarez *** based on an electrostatic MEMS generates fast and controllable actuation with low power *** utilization of metasurfaces–ultrathin and subwavelength-patterned diffractive optics–as optical elements greatly reduces the device volume compared to systems using conventional freeform *** entire MEMS Alvarez metalens is fully compatible with modern semiconductor fabrication technologies,granting it the potential to be mass-produced at a low unit *** the reported prototype operating at 1550 nm wavelength,a total uniaxial displacement of 6.3µm was achieved in the Alvarez metalens with a direct-current(DC)voltage application up to 20V,which modulated the focal position within a total tuning range of 68µm,producing more than an order of magnitude change in the focal length and a 1460-diopter change in the optical *** MEMS Alvarez metalens has a robust design that can potentially generate a much larger tuning range without substantially increasing the device volume or energy consumption,making it desirable for a wide range of imaging and display applications.

关键词： electrostatic optics adapted

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Pixelation with concentration-encoded effective photons for molecular optical sectioning microscopy

arXiv

引用

arXiv 2023年

作者： Wang, Geng Iyer, Rishyashring R. Sorrells, Janet E. Aksamitiene, Edita Chaney, Eric J. Renteria, Carlos A. Park, Jaena Shi, Jindou Sun, Yi Boppart, Stephen A. Tu, Haohua Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Bioengineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States

Quality control in molecular optical sectioning microscopy is indispensable for transforming acquired digital images from qualitative descriptions to quantitative data. Although numerous tools, metrics, and phantoms have been developed, accurate quantitative comparisons of data from different microscopy systems with diverse acquisition conditions remains a challenge. Here, we develop a simple tool based on an absolute measurement of bulk fluorophore solutions with related Poisson photon statistics, to overcome this obstacle. Demonstrated in a prototypical multiphoton microscope, our tool unifies the unit of pixelated measurement to enable objective comparison of imaging performance across different modalities, microscopes, components/settings, and molecular targets. The application of this tool in live specimens identifies an attractive methodology for quantitative imaging, which rapidly acquires low signal-to-noise frames with either gentle illumination or low-concentration fluorescence labeling. © 2023, CC BY.

关键词： Metadata

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Photon avalanche-driven multicolor emission: yttrium vanadate upconversion phosphors for optical thermometry, forensics, and healing light applications

引用

Chemical engineering Journal 2025年 516卷

作者： Pavitra, Eluri Antony, Lintymol Park, Jin Young Hwang, Seung Kyu Lee, Jeong-Hwan Chandra, Gogineni Rajesh Basaveswara Rao, M.V. Raju, Ganji Seeta Rama Han, Young-Kyu Huh, Yun Suk NanoBio High-Tech Materials Research Center Department of Biological Sciences and Bioengineering Inha University Incheon22212 Korea Republic of 3D Convergence Center Inha University Incheon22212 Korea Republic of Department of Energy and Materials Engineering Dongguk University-Seoul Seoul04620 Korea Republic of Department of Electrical Electronics and Software Engineering Pukyong National University Yongdang Campus Busan48547 Korea Republic of Department of Materials Science and Engineering Inha University Incheon22212 Korea Republic of Program in Semiconductor Convergence Inha University Incheon22212 Korea Republic of Department of Computer Science and Engineering Vignan's Lara Institute of Technology & Science Andhra Pradesh Guntur India Department of Chemistry Krishna University Andhra Pradesh Machillipatnam521001 India

The exploration of photon upconversion has led to the development of multifunctional lanthanide-based materials, particularly through the mechanism of photon avalanche, marking a transformative advancement in material science. In this study, yttrium vanadate upconversion nanocrystalline phosphors (UCNCPs) activated by Ho3+/Er3+/Tm3+/Yb3+ ions are reported. These UCNCPs demonstrate a remarkable ability in the photon avalanche, offering highly intense and tunable emissions across the visible spectrum at room temperature under low excitation power of 980 nm laser. The average number of photons involved in the UC process at threshold pump power, highlighting the intricate interplay of cross-relaxation and energy transfer loops in avalanche mechanism. Notably, these UCNCPs have shown exceptional temperature sensing capabilities, where non-thermally coupled levels of the Ho3+ and Tm3+ ions provide higher relative sensitivity and accuracy than thermally coupled levels of Er3+ ions. The versatility of these UCNCPs is further established by their application in solid-state lighting, where they can produce vibrant red, green, blue, and warm-white light, and in security, serving as multi-level anti-counterfeiting inks that respond to 980 nm laser illumination. These developments not only pave the way for more energy-efficient lighting solutions but also offer new avenues for enhancing the security of valuable items. The temperature sensing capabilities of these phosphors add another layer of functionality, making them ideal for high-tech applications ranging from medical diagnostics to environmental monitoring. © 2025 Elsevier B.V.

关键词： Phosphors

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Fiber-optic nonlinear wavelength converter for adaptive femtosecond biophotonics

arXiv

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arXiv 2023年

作者： Wang, Geng Shi, Jindou Iyer, Rishyashring R. Sorrells, Janet E. Tu, Haohua Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Bioengineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States

Broad and safe access to ultrafast laser technology has been hindered by the absence of optical fiber-delivered pulses with tunable central wavelength, pulse repetition rate, and pulse width in the picosecond-femtosecond regime. To address this long-standing obstacle, we developed a reliable accessory for femtosecond ytterbium fiber chirped pulse amplifiers, termed as fiber-optic nonlinear wavelength converter (FNWC), as an adaptive optical source for the emergent field of femtosecond biophotonics. This accessory embowers the fixed-wavelength laser to produce fiber delivered ~20 nJ pulses with central wavelength across 950-1150 nm, repetition rate across 1-10 MHz, and pulse width across 40-400 fs, with a long-term stability of >2000 hrs. As a prototypical label-free application in biology and medicine, we demonstrate the utility of FNWC in real-time intravital imaging synergistically integrated with modern machine learning and large-scale fluorescence lifetime imaging microscopy. © 2023, CC BY.

关键词： Nonlinear optics

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