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CLEO: QELS_Fundamental Science, QELS 2022

作者： Luo, Yi Mengu, Deniz 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

A cascadable, all-optical NAND gate based on diffractive networks is presented. The resulting NAND design was cascaded by projecting the output field of one diffractive gate onto another, all-optically performing logi...

ISBN: (纸本)9781557528209

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Diffractive optical imagers can see through random unknown diffusers

Diffractive optical imagers can see through random unknown d...

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Frontiers in Optics, FiO 2022

作者： Li, Yuhang Luo, Yi Bai, Bijie 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

We provide a comprehensive design guide for robust and generalizable diffractive imagers to all-optically see through random unknown diffusers at the speed of light, without needing any digital computation or reconstr...

ISBN: (纸本)9781557528209

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Seeing through unknown, random diffusers using diffractive optical networks

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

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CLEO: QELS_Fundamental Science, QELS 2022

作者： Luo, Yi Zhao, Yifan Li, Jingxi Çetintaş, Ege Rivenson, Yair 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

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: (纸本)9781557528209

关键词： Deep neural networks

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Classification and reconstruction of spatially overlapping phase objects through diffractive networks

Classification and reconstruction of spatially overlapping p...

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Computational Optical Sensing and Imaging, COSI 2022

作者： Mengu, Deniz Veli, Muhammed Rivenson, Yair 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

We present diffractive networks that can all-optically classify spatially-overlapping phase objects. Individual phase images of the overlapping objects are also reconstructed using electronic networks that process the...

ISBN: (纸本)9781557528209

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Diffractive Networks All-Optically Reconstruct Holograms

Diffractive Networks All-Optically Reconstruct Holograms

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CLEO: QELS_Fundamental Science, QELS 2022

作者： Rahman, Md Sadman Sakib 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

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. © Optica Publish... 详细信息

ISBN: (纸本)9781557528209

关键词： Holograms

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Bioinspired UV-Visible Multispectral Imaging Sensor Enabled by Perovskite Nanocrystal Coating

Bioinspired UV-Visible Multispectral Imaging Sensor Enabled ...

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2023 Imaging Systems and Applications, IS 2023 in Optica Imaging Congress - Part of Imaging and Applied Optics Congress 2023

作者： Chen, Cheng Wang, Ziwen Wu, Jiajing Deng, Zhengtao Zhang, Tao Zhu, Zhongming Jin, Yifei Lew, Benjamin Srivastava, Indrajit Liang, Zuodong Nie, Shuming Gruev, Viktor 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 College of Engineering and Applied Sciences Nanjing University Jiangsu Nanjing China Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign UrbanaIL61801 United States

Inspired by the visual system of Papilio xuthus butterfly, w e f abricated a ultraviolet-visible multispectral imager which combines perovskite nanocrystals and vertically stacked silicon photodetectors. High-resoluti... 详细信息

ISBN: (纸本)9781957171289

关键词： Nanocrystals

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Multiscale multi-functional phase imaging platform for cell and tissue characterization

Multiscale multi-functional phase imaging platform for cell ...

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IEEE Photonics Conference (IPC)

作者： Hongqiang Ma Phuong Nguyen Yang Liu Department of Bioengineering Beckman Institute for Advanced Science and Technology University of Illinois Urbana-Champaign Urbana IL USA Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Urbana IL USA

ISBN: (数字)9798350361957

ISBN: (纸本)9798350361964

Phase Imaging offers a label-free approach to non-invasively characterize cellular processes and tissue architecture by exploiting their refractive index based intrinsic contrast in their natural states. In this study, we present a multiscale phase imaging system that bridges mesoscale and nanoscale imaging. This system shows the capability for large-scale, simultaneous tracking of live-cell morphodynamics, capturing sub-cellular details across thousands of cells as they develop resistance to chemotherapy drugs and the ability to reveal sub-cellular features in pathological tissue.

关键词： Pathology Chemotherapy Optical microscopy Imaging Refractive index Optical variables control Optical imaging Nanoscale devices Optical refraction Photonics

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3D direct printing of mechanical and biocompatible hydrogel meta-structures

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Bioactive Materials 2022年第4期7卷 48-55页

作者： Lei Zhang Wenhan Lee Xinhao Li Yanhui Jiang Nicholas Xuanlai Fang Guohao Dai Yongmin Liu Department of Mechanical&Industrial Engineering Northeastern UniversityBostonMA02115United States State Key Laboratory of Primate Biomedical Research Institute of Primate Translational MedicineKunming University of Science and TechnologyKunming650500China Department of Bioengineering Northeastern UniversityBostonMA02115United States Department of Mechanical Engineering Massachusetts Institute of TechnologyCambridgeMA02139United States Department of Electrical and Computer Engineering Northeastern UniversityBostonMA02115United States

Direct Ink Writing(DIW)has demonstrated great potential as a versatile method to 3D print multifunctional *** this work,we report the implementation of hydrogel meta-structures using DIW at room temperature,which seamlessly integrate large specific surface areas,interconnected porous characteristics,mechanical toughness,biocompatibility,and water absorption and retention *** but hydrophobic polymers and weakly crosslinked nature-origin hydrogels form a balance in the self-supporting ink,allowing us to directly print complex meta-structures without sacrificial materials and heating ***,the mixed bending or stretching of symmetrical re-entrant cellular lattices and the unique curvature patterns are combined to provide little lateral expansion and large compressive energy absorbance when external forces are applied on the printed *** addition,we have successfully demonstrated ear,aortic valve conduits and hierarchical *** anticipate that the reported 3D meta-structured hydrogel would offer a new strategy to develop functional biomaterials for tissue engineering applications in the future.

关键词： Direct ink writing Gyroid meta-structure Mechanical-functional integration Naturally derived hydrogel

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Multi-level, Forming Free, Bulk Switching Trilayer RRAM for Neuromorphic Computing at the Edge

arXiv

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arXiv 2023年

作者： Park, Jaeseoung Kumar, Ashwani Zhou, Yucheng Oh, Sangheon Kim, Jeong-Hoon Shi, Yuhan Jain, Soumil Hota, Gopabandhu Nagle, Amelie L. Schuman, Catherine D. Cauwenberghs, Gert Kuzum, Duygu Department of Electrical and Computer Engineering University of California San DiegoCA United States Department of Bioengineering University of California San DiegoCA United States Department of Computer Science Massachusetts Institute of Technology MA United States Department of Electrical Engineering and Computer Science University of Tennessee TN United States

Resistive memory-based reconfigurable systems constructed by CMOS-RRAM integration hold great promise for low energy and high throughput neuromorphic computing. However, most RRAM technologies relying on filamentary switching suffer from variations and noise leading to computational accuracy loss, increased energy consumption, and overhead by expensive program and verify schemes. Low ON-state resistance of filamentary RRAM devices further increases the energy consumption due to high-current read and write operations, and limits the array size and parallel multiply & accumulate operations. High-forming voltages needed for filamentary RRAM are not compatible with advanced CMOS technology nodes. To address all these challenges, we developed a forming-free and bulk switching RRAM technology based on a trilayer metal-oxide stack. We systematically engineered a trilayer metal-oxide RRAM stack and investigated the switching characteristics of RRAM devices with varying thicknesses and oxygen vacancy distributions across the trilayer to achieve reliable bulk switching without any filament formation. We demonstrated bulk switching operation at megaohm (MΩ) regime with high current nonlinearity and programmed up to 100 levels without compliance current. We developed a neuromorphic compute-in-memory platform based on trilayer bulk RRAM crossbars by combining energy-efficient switched-capacitor voltage sensing circuits with differential encoding of weights to experimentally demonstrate high-accuracy matrix-vector multiplication. We showcased the computational capability of bulk RRAM crossbars by implementing a spiking neural network model for an autonomous navigation/racing task. Our work addresses challenges posed by existing RRAM technologies and paves the way for neuromorphic computing at the edge under strict size, weight, and power constraints. © 2023, CC BY.

关键词： RRAM

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Surgical Suturing Skill Assessment Using Estimated Hand Roll Angle from a Deep-learning computer Vision Algorithm

Surgical Suturing Skill Assessment Using Estimated Hand Roll...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Jianxin Gao Amir Mehdi Shayan Simar P. Singh Joe Bible Ravikiran Singapogu Richard E. Groff Department of Electrical and Computer Engineering Clemson University Clemson SC USA Department of Bioengineering Clemson University Clemson SC USA School of Mathematical and Statistical Sciences Clemson University Clemson SC USA

ISBN: (数字)9798350371499

ISBN: (纸本)9798350371505

This paper proposes a deep-learning computer vision algorithm to estimate hand roll angles for metric-based assessment of surgical suturing skills. The number of rolls metric, previously calculated directly from IMU data, counts the number of hand roll reversals during a single suture. To calculate this metric using computer vision, we apply a deep-learning algorithm that can reliably estimate hand roll angles after training on suturing videos collected on the SutureCoach simulator. Results show that the estimation accuracy of the deep-learning algorithm is robust to different video backgrounds. The number of rolls metrics were used to analyze suturing performance in the SutureCoach dataset, which includes attending and resident surgeons and novices. The means of number of rolls based on computer vision differs between most skill levels at both surface and depth conditions, a pattern which holds for number of rolls based on the IMU as well. The proposed algorithm provides a solution for non-contact hand roll angle estimation, which opens up the possibility of inter-operative surgical skill assessment. The code is available at https://***/axin233/hand_roll_estimation

关键词： Measurement Training computer vision Visualization Tracking Surgery Estimation Cameras Motion analysis Videos

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