检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Liao, Congyu Cao, Xiaozhi Iyer, Siddharth Srinivasan Schauman, Sophie Zhou, Zihan Yan, Xiaoqian Chen, Quan Li, Zhitao Wang, Nan Gong, Ting Wu, Zhe He, Hongjian Zhong, Jianhui Yang, Yang Kerr, Adam Grill-Spector, Kalanit Setsompop, Kawin Department of Radiology Stanford University StanfordCA United States Department of Electrical Engineering Stanford University StanfordCA United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA United States Center for Brain Imaging Science and Technology College of Biomedical Engineering & Instrument Science Zhejiang University Zhejiang Hangzhou China Department of Psychology Stanford University StanfordCA United States Institute of Science and Technology for Brain-Inspired Intelligence Fudan University Shanghai China Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Harvard Medical School CharlestownMA United States Techna Institute University Health Network TorontoON Canada School of Physics Zhejiang University Zhejiang Hangzhou China Department of Imaging Sciences University of Rochester RochesterNY United States Department of Radiology and Biomedical Imaging University of California San FranciscoCA United States Stanford Center for Cognitive and Neurobiological Imaging Stanford University StanfordCA United States

Purpose: This study aims to develop a high-resolution whole-brain multi-parametric quantitative MRI approach for simultaneous mapping of myelin-water fraction (MWF), T1, T2, and proton-density (PD), all within a clinically feasible scan time. Methods: We developed 3D ViSTa-MRF, which combined Visualization of Short Transverse relaxation time component (ViSTa) technique with MR Fingerprinting (MRF), to achieve high-fidelity whole-brain MWF and T1/T2/PD mapping on a clinical 3T scanner. To achieve fast acquisition and memory-efficient reconstruction, the ViSTa-MRF sequence leverages an optimized 3D tiny-golden-angle-shuffling spiral-projection acquisition and joint spatial-temporal subspace reconstruction with optimized preconditioning algorithm. With the proposed ViSTa-MRF approach, high-fidelity direct MWF mapping was achieved without a need for multi-compartment fitting that could introduce bias and/or noise from additional assumptions or priors. Results: The in-vivo results demonstrate the effectiveness of the proposed acquisition and reconstruction framework to provide fast multi-parametric mapping with high SNR and good quality. The in-vivo results of 1mm- and 0.66mm-iso datasets indicate that the MWF values measured by the proposed method are consistent with standard ViSTa results that are 30x slower with lower SNR. Furthermore, we applied the proposed method to enable 5-minute whole-brain 1mm-iso assessment of MWF and T1/T2/PD mappings for infant brain development and for post-mortem brain samples. Conclusions: In this work, we have developed a 3D ViSTa-MRF technique that enables the acquisition of whole-brain MWF, quantitative T1, T2, and PD maps at 1mm and 0.66mm isotropic resolution in 5 and 15 minutes, respectively. This advancement allows for quantitative investigations of myelination changes in the brain. © 2023, CC BY.

关键词： Mapping

来源：评论

学校读者我要写书评

暂无评论

Design and Experimental Evaluation of a Haptic Robot-Assisted System for Femur Fracture Surgery

arXiv

引用

arXiv 2023年

作者： Alruwaili, Fayez H. Clancy, Michael P. Saeedi-Hosseiny, Marzieh S. Logar, Jacob A. Papachristou, Charalampos Haydel, Christopher Parvizi, Javad Iordachita, Iulian I. Abedin-Nasab, Mohammad H. The Biomedical Engineering Department Rowan University GlassboroNJ08028 United States The Electrical and Computer Engineering Department Rowan University GlassboroNJ08028 United States The College of Science & Mathematics Rowan University GlassboroNJ08028 United States Virtua Health MoorestownNJ08057 United States Rothman Orthopedic Institute Thomas Jefferson University Hospital PhiladelphiaPA United States The Laboratory for Computational Sensing and Robotics Johns Hopkins University BaltimoreMD21218 United States

In the face of challenges encountered during femur fracture surgery, such as the high rates of malalignment and X-ray exposure to operating personnel, robot-assisted surgery has emerged as an alternative to conventional state-of-the-art surgical methods. This paper introduces the development of Robossis, a haptic system for robot-assisted femur fracture surgery. Robossis comprises a 7-DOF haptic controller and a 6-DOF surgical robot. A unilateral control architecture is developed to address the kinematic mismatch and the motion transfer between the haptic controller and the Robossis surgical robot. A real-time motion control pipeline is designed to address the motion transfer and evaluated through experimental testing. The analysis illustrates that the Robossis surgical robot can adhere to the desired trajectory from the haptic controller with an average translational error of 0.32 mm and a rotational error of 0.07°. Additionally, a haptic rendering pipeline is developed to resolve the kinematic mismatch by constraining the haptic controller’s (user’s hand) movement within the permissible joint limits of the Robossis surgical robot. Lastly, in a cadaveric lab test, the Robossis system assisted surgeons during a mock femur fracture surgery. The result shows that Robossis can provide an intuitive solution for surgeons to perform femur fracture surgery. Copyright © 2023, The Authors. All rights reserved.

关键词： Robotic surgery

来源：评论

学校读者我要写书评

暂无评论

All-optical Raman-based noise spectroscopy of solid-state spin qubits

All-optical Raman-based noise spectroscopy of solid-state sp...

引用

Conference on Quantum Information and Measurement, ICQI 2021

作者： Farfurnik, Demitry Singh, Harjot Luo, Zhouchen Bracker, Allan S. Carter, Samuel G. Pettit, Robert M. Waks, Edo Department of Electrical and Computer Engineering Institute for Research in Electronics and Applied Physics Joint Quantum Institute University of Maryland College ParkMD United States Naval Research Laboratory WashingtonDC United States Intelligence Community Postrdoctoral Research Fellowship Program University of Maryland College ParkMD United States

We introduce an all-optical approach for noise spectroscopy of solid-state spin qubits, based on Raman control and the Carr-Purcell-Meiboom-Gill pulse sequences, and use it to extract the noise spectra of self-assembl... 详细信息

ISBN: (纸本)9781957171012

关键词： Semiconductor quantum dots

来源：评论

学校读者我要写书评

暂无评论

Label-free SARS-CoV-2 detection and classification using phase imaging with computational specificity

引用

Light(Science & Applications) 2021年第9期10卷 1797-1808页

作者： Neha Goswami Yuchen R.He Yu-Heng Deng Chamteut Oh Nahil Sobh Enrique Valera Rashid Bashir Nahed Ismail Hyunjoon Kong Thanh H.Nguyen Catherine Best-Popescu Gabriel Popescu Department of Bioengineering University of Illinois Urbana-ChampaignUrbanaIllinois61801USA Beckman Institute of Advanced Science and Technology University of Illinois Urbana-ChampaignUrbanaIllinois61801USA Department of Electrical and Computer Engineering University of Illinois Urbana-ChampaignUrbanaIllinois61801USA Department of Chemical and Biomolecular Engineering University of Illinois at Urbana-ChampaignUrbanaIL61801USA Department of Civil and Environmental Engineering University of Illinois at Urbana-ChampaignUrbanaIL61801USA NCSA Center for Artificial Intelligence Innovation University of Illinois at Urbana-ChampaignUrbanaIL61801USA Holonyak Micro and Nanotechnology Laboratory University of Illinois at Urbana-ChampaignUrbanaIllinois61801USA Biomedical Research Center Carle Foundation Hospital509W University Ave.UrbanaIllinois61801USA Carle Illinois College of Medicine 807 South Wright St.UrbanaIllinois61801USA Mayo-Illinois Alliance for Technology Based Healthcare UrbanaIllinois61801USA Department of Pathology College of MedicineUniversity of Illinois at ChicagoChicagoILUSA

Efforts to mitigate the COVID-19 crisis revealed that fast,accurate,and scalable testing is crucial for curbing the current impact and that of future *** propose an optical method for directly imaging unlabeled viral particles and using deep learning for detection and *** ultrasensitive interferometric method was used to image four virus types with nanoscale optical path-length *** these data with fluorescence images for ground truth,we trained semantic segmentation models based on U-Net,a particular type of convolutional neural *** trained network was applied to classify the viruses from the interferometric images only,containing simultaneously SARS-CoV-2,H1N1(influenza-A virus),HAdV(adenovirus),and ZIKV(Zika virus).Remarkably,due to the nanoscale sensitivity in the input data,the neural network was able to identify SARS-CoV-2 *** other viruses with 96%*** inference time for each image is 60 ms,on a common graphic-processing *** approach of directly imaging unlabeled viral particles may provide an extremely fast test,of less than a minute per *** the imaging instrument operates on regular glass slides,we envision this method as potentially testing on patient breath *** necessary high throughput can be achieved by translating concepts from digital pathology,where a microscope can scan hundreds of slides automatically.

关键词： testing neural hundreds

来源：评论

学校读者我要写书评

暂无评论

Experimental results from the characterization of a 32-channels mixed-signal processor for the GAPS experiment

Experimental results from the characterization of a 32-chann...

引用

IEEE Symposium on Nuclear Science (NSS/MIC)

作者： E. Riceputi M. Manghisoni V. Re L. Ghislotti P. Lazzaroni L. Ratti L. Fabris M. Boezio G. Zampa M. Xiao E. Cavazzuti V. Vagelli Department of Engineering and Applied Sciences Università Degli Studi di Bergamo Bergamo Italy Pavia Section Istituto Nazionale Fisica Nucleare Pavia Italy Department of Electrical Computer and Biomedical Engineering Università di Pavia Pavia Italy Oak Ridge National Laboratory Oak Ridge Tennessee United States of America Trieste Section Istituto Nazionale Fisica Nucleare Trieste Italy Massachussetts Institute of Technology Cambridge Massachusetts United States of America Agenzia Spaziale Italiana Roma Italy

This work describes the experimental results obtained from the characterization of a 32-channels readout ASIC that is the core of a module composed by 4 Lithium-drifted Silicon, Si(Li), detectors. The module is the building block of a tracker in an upcoming balloon experiment. The activity is carried out within the General AntiParticle Spectrometer (GAPS) international collaboration, whose objective is the indirect detection of dark matter through the detection of antiparticles present in cosmic rays at low energies. The balloon flight is foreseen in 2024 from the McMurdo station in Antarctica. The ASIC is designed in a 180 nm CMOS technology and has 32 low-noise analog readout channels featuring a dynamic compression of the signal, an 11-bit SAR ADC, and a digital back-end section responsible for channel setting and for sending digital information to the data acquisition system of the tracker. This work has a twofold goal: it intends on the one hand to verify the performance of the circuit, on the other to select at least 300 good samples to be used for the assembly of the GAPS Si(Li) tracker.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Tuning light emission crossovers in atomic-scale aluminum plasmonic tunnel junctions

arXiv

引用

arXiv 2022年

作者： Zhu, Yunxuan Cui, Longji Abbasi, Mahdiyeh Natelson, Douglas Department of Physics and Astronomy Rice University HoustonTX77005 United States Paul M. Rady Department of Mechanical Engineering University of Colorado BoulderCO80309 United States Materials Science and Engineering Program University of Colorado BoulderCO80309 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Department of Materials Science and Nanoengineering Rice University HoustonTX77005 United States

Atomic sized plasmonic tunnel junctions are of fundamental interest, with great promise as the smallest on-chip light sources in various optoelectronic applications. Several mechanisms of light emission in electrically driven plasmonic tunnel junctions have been proposed, from single-electron or higher order multi-electron inelastic tunneling to recombination from a steady-state population of hot carriers. By progressively altering the tunneling conductance of an aluminum junction, we tune the dominant light emission mechanism through these possibilities for the first time, finding quantitative agreement with theory in each regime. Improved plasmonic resonances in the energy range of interest increase photon yields by two orders of magnitude. These results demonstrate that the dominant emission mechanism is set by a combination of tunneling rate, hot carrier relaxation timescales, and junction plasmonic properties. Copyright © 2022, The Authors. All rights reserved.

关键词： Tunnel junctions

来源：评论

学校读者我要写书评

暂无评论

Super-resolution Radial Fluctuations Enables Polarization-resolved Nonlinear Optical Nanoscopy

arXiv

引用

arXiv 2025年

作者： Harvey, MacAulay Cisek, Richard Al-Turk, Sarry Ruda, Harry E. Kreplak, Laurent Tokarz, Danielle Department of Chemistry Saint Mary’s University 923 Robie Street HalifaxNSB3H 3C3 Canada Centre for Advanced Nanotechnology University of Toronto 170 College Street TorontoONM5S 3E4 Canada Department of Materials Science and Engineering University of Toronto 184 College Street TorontoONM5S 3E4 Canada Department of Electrical and Computer Engineering University of Toronto 10 Kings College Road TorontoONM5S 3G4 Canada Department of Physics and Atmospheric Science School of Biomedical Engineering Dalhousie University HalifaxNSB3H 4J5 Canada

Second harmonic generation microscopy (SHG) is a powerful imaging modality which has found applications in investigating both biological and synthetic nanostructures. Like all optical microscopy techniques, the resolution of SHG is limited to approximately half the wavelength of the excitation light. Because of this several groups have proposed techniques to enable super-resolution SHG imaging. However, these techniques often involve quite complicated optical setups compared to standard SHG microscopes, a major impediment towards more widespread utilization. Here we apply super-resolution radial fluctuations (SRRF), a commonly used technique for super-resolution fluorescence imaging, to enable super-resolution SHG microscopy. By imaging individual nanostructures, we demonstrate that SRRF can provide resolution enhancement of up to 3× compared to a laser scanning SHG microscope, which is comparable to the best resolution enhancement reported in the literature. Additionally, we show that SRRF maintains the polarization dependence of SHG, therefore enabling super-resolution polarization SHG imaging. Finally, we perform SRRF processing on third harmonic generation images to demonstrate the significant potential of SRRF for other super-resolution nonlinear optical microscopy. Importantly, since SRRF can achieve super-resolution purely through image processing, the technique demonstrated here could be used to enhance the resolution of images obtained using a wide variety of nonlinear optical microscopy setups including both laser scanning and widefield configurations. Copyright © 2025, The Authors. All rights reserved.

关键词： Nonlinear optics

来源：评论

学校读者我要写书评

暂无评论

Joint spatio-temporal neural source reconstruction using electroencephalography and near-infrared spectroscopy

Joint spatio-temporal neural source reconstruction using ele...

引用

Clinical and Translational Biophotonics, Translational 2020

作者： Cao, Jiaming Huppert, Theodore Grover, Pulkit Kainerstorfer, Jana M. Department of Biomedical Engineering Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213 United States Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA15260 United States Department of Electrical and Computer Engineering Carnegie Mellon University 5000 Forbes Avenue PittsburghPA15213 United States Carnegie Mellon Neuroscience Institute Carnegie Mellon University 4400 Fifth Avenue PittsburghPA15213 United States

Electroencephalography (EEG) and near-infrared spectroscopy (NIRS) are commonly used for neural source reconstruction, but have limited spatial or temporal resolution. Using NIRS reconstruction as a spatial prior for ... 详细信息

ISBN: (纸本)9781943580743

关键词： Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

Depression Severity Identification Based on Shallow 2d Self-Attention-Cnn Using Eeg Functional Connectivity Network

SSRN

引用

SSRN 2024年

作者： Zhou, Yihan Yu, Xiaokang Lin, Huiping Li, Rihui Liang, Jiuxing Shi, Xue Luo, Yuxi School of Biomedical Engineering Shenzhen Campus of Sun Yat-sen University Guangdong Shenzhen518100 China Center for Cognitive and Brain Sciences Department of Electrical and Computer Engineering University of Macau Taipa China Key Laboratory of Brain Cognition and Education Science Ministry of Education Institute for Brain Research and Rehabilitation Guangdong Key Laboratory of Mental Health and Cognitive Science South China Normal University China Department of Neurology Shenzhen People's Hospital The Second Clinical Medical College Jinan University The First Affiliated Hospital Southern University of Science and Technology Shenzhen China Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province Sun Yat-sen University Guangdong Shenzhen518100 China

Background and objectives: Depression inflicts significant harm on both society and family. Previous studies have indicated that the functional network of EEG signals worked well in recognizing major depression. This study aims to further identify depression severities and characterize their EEG functional network difference by designing a deep learning strategy and a corresponding visualization ***: Rest state EEG recordings from 30 healthy controls, 35 mild depressed and 26 severe depressed patients were included. Weighted phase lag indexes were computed across four frequency sub-bands to delineate the functional connectivity of EEG networks, serving as the input matrix. To better adapt volume conduction effects, a shallow CNN-based incorporated with 2D Self-Attention architecture was designed, enabling the model to capture information across diverse spans and scales within the functional connectivity (FC) matrix. Leveraging the Grad-CAM algorithm, the model highlighted crucial FCs and corresponding EEG pairs for classification. Finally, the changes of EEG FC network across depression severities were statistically analyzed and ***: An accuracy of 89.2% was achieved in tri-classification of 10-second EEG segments using 52 EEG channels, remaining high at 84.1% with 30 selected channels. Notably, the investigation revealed that significant FC changes from mild to severe depression did not exhibit a simple or monotonous ***: This research presented a directly measured methodology to identify depression severity, vital for informing prevention and therapeutic interventions. Furthermore, the findings shed light on the evolving patterns of brain function as depression progresses. The proposed deep learning model and channel selection algorithm offer potential applications beyond this study, promising broader utility in EEG-based research endeavors. © 2024, The Authors. All rights reserved.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Brain MRI Synthesis Using Stylegan2-ADA

Brain MRI Synthesis Using Stylegan2-ADA

引用

IEEE International Symposium on biomedical Imaging

作者： Matteo Lai Chiara Marzi Mario Mascalchi Stefano Diciotti Department of Electrical Electronic and Information Engineering "Guglielmo Marconi" - DEI University of Bologna Cesena Italy Alma Mater Research Institute for Human-Centered Artificial Intelligence University of Bologna Bologna Italy Department of Statistics Computer Science Applications "G. Parenti" University of Firenze Firenze Italy Experimental and Clinical Biomedical Sciences "Mario Serio" University of Florence Firenze Italy Clinical Epidemiology Unit Institute for Cancer Research Prevention and Clinical Network (ISPRO) Florence Italy

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

Deep learning (DL) applications in the medical field often face challenges related to limited data availability, resulting in issues like overfitting and imbalanced datasets. Synthetic data offers a promising solution to these problems by enabling data augmentation and enhancing the performance of DL models. In this study, we trained the state-of-the-art generative model StyleGAN2-ADA on 1412 images from the Alzheimer’s disease neuroimaging initiative (ADNI) dataset to generate synthetic slices of T1-weighted brain MRI of healthy subjects. The quality of the synthetic images has been evaluated through quantitative and qualitative assessments, including a visual Turing test conducted by an expert observer with 2000 images. The observer achieved an accuracy of 52.95%, indicative of a performance level comparable to random guessing. These results demonstrate the capability of StyleGAN2-ADA to generate anatomically relevant synthetic brain MRI data.

关键词： Neuroimaging Visualization Magnetic resonance imaging Observers Brain modeling Data augmentation Data models

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：