检索结果-内蒙古大学图书馆

Laser Machined Fiber‑Based Microprobe: Application in Microscale Electroporation

Advanced Fiber Materials 2022年第4期4卷 859-872页

作者： Jongwoon Kim Yajun Zhao Shuo Yang Ziang Feng Anbo Wang Rafael V.Davalos Xiaoting Jia Bradley Department of Electrical and Computer Engineering Virginia TechBlacksburgVA 24060USA Department of Biomedical Engineering and Mechanics Virginia TechBlacksburgVA 24061USA

Microscale electroporation devices are mostly restricted to in vitro experiments(i.e.,microchannel and microcapillary).Novel fiber-based microprobes enable in vivo microscale electroporation and arbitrarily select the cell groups of interest to *** developed a flexible,fiber-based microscale electroporation device through a thermal drawing process and femtosecond laser micromachining *** fiber consists of four copper electrodes(80μm),one microfluidic channel(30μm),and has an overall diameter of 400μ*** dimensions of the exposed electrodes and channel were customizable through a delicate femtosecond laser *** feasibility of the fiber probe was validated through numerical simulations and in vitro *** reversible and irreversible microscale electroporation was observed in a 3D collagen scaffold(seeded with U251 human glioma cells)using fluorescent *** ablation regions were estimated by performing the covariance error ellipse method and compared with the numerical *** computational and experimental results of the working fiber-based microprobe suggest the feasibility of in vivo microscale electroporation in space-sensitive areas,such as the deep brain.

关键词： Fiber probe Polymer Micromachine Irreversible electroporation Reversible electroporation Microscale electroporation

来源：评论

学校读者我要写书评

暂无评论

Modified CNN VoxNet Based Depthwise Separable Convolution for Voxel-Driven Body Orientation Classification

Modified CNN VoxNet Based Depthwise Separable Convolution fo...

引用

2024 IEEE International Conference on Imaging Systems and Techniques, IST 2024

作者： Riansyah, Moch. Iskandar Putra, Oddy Virgantara Priyadi, Ardyono Sardjono, Tri Arief Yuniarno, Eko Mulyanto Purnomo, Mauridhi Hery Institut Teknologi Sepuluh Nopember Department of Electrical Engineering Indonesia Telkom University Department of Electrical Engineering Indonesia Universitas Darussalam Gontor Department of Informatics Ponorogo Indonesia Institut Teknologi Sepuluh Nopember Department of Electrical Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Biomedical Engineering Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Electrical Engineering Department of Computer Engineering Surabaya Indonesia

ISBN: (纸本)9798350378214

In this research, LiDAR sensor technology introduces a new representation of point cloud data for tasks in 3D object recognition. Point clouds provide rich information that can be utilized to predict the orientation pose of the human body. The orientation of the human body is crucial for various needs such as autonomous vehicles, robotics, and human activity monitoring. However, the inherently unstructured nature and permutation invariance of point cloud data pose significant challenges in accurately predicting human body orientation using 3D data. In this paper, we propose a solution by introducing a volumetric method based on CNN to effectively recognize human body ori-entation. A novel approach is proposed by embedding depthwise sparse convolution into 2D CNN to process voxel data of human body orientation. We evaluate the performance using KITTI data divided into four orientation classes: east, west, north, and south. Additionally, we compare it with other architectures using the ModelNet10 and ModelNet40 datasets. The comparison with other architectures shows superior performance with accuracies of 84.31 % for the KITTI dataset, 86.67 % for ModelNet10, and 75.20 % for ModelNet40. This evidence strongly supports the effectiveness of our proposed method, highlighting its potential in enhancing 3D object recognition systems significantly. © 2024 IEEE.

关键词： CNN depthwise sparse convolution human body orientation lidar point cloud

来源：评论

学校读者我要写书评

暂无评论

Extracting 3D Information from Widefield Birefringence Microscopy Images of Sparse Myelinated Fibers in Human Brain Gray Matter

Extracting 3D Information from Widefield Birefringence Micro...

引用

Microscopy Histopathology and Analytics, Microscopy 2024 - Part of Optica Biophotonics Congress: biomedical Optics

作者： Novoseltseva, Anna Xie, Ting Bigio, Irving J. Department of Biomedical Engineering Boston University BostonMA02215 United States Department of Electrical & Computer Engineering Boston University BostonMA02215 United States

We report the application of widefield birefringence microscopy for 3D rendering of sparse myelinated fibers in human brain gray matter. This inexpensive and simple method offers the potential to inform studies of the... 详细信息

ISBN: (纸本)9781957171340

关键词： Birefringence

来源：评论

学校读者我要写书评

暂无评论

Mode-Division Multiplexing at Visible Wavelengths

Mode-Division Multiplexing at Visible Wavelengths

引用

2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Shah, Priyansh Mellouk, Elias Ben Levine, Jeremy Mohanty, Aseema Department of Electrical and Computer Engineering Tufts University MedfordMA02155 United States Department of Biomedical Engineering Tufts University MedfordMA02155 United States

We demonstrate mode-division multiplexing at visible wavelengths (473 nm) for the first time using adiabatic mode couplers. We measure less than -15 dB and -20 dB crosstalk for TE2 and TE3 higher-order mode couplers, ... 详细信息

ISBN: (纸本)9781957171395

关键词： Laser beams

来源：评论

学校读者我要写书评

暂无评论

Mode-Division Multiplexing at Visible Wavelengths

Mode-Division Multiplexing at Visible Wavelengths

引用

CLEO: Science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

关键词： Tellurium compounds

来源：评论

学校读者我要写书评

暂无评论

On-chip hyperspectral detectors for fluorescence lifetime imaging 9

On-chip hyperspectral detectors for fluorescence lifetime im...

引用

High-Speed biomedical Imaging and Spectroscopy IX 2024

作者： Ahamed, Ahasan Rawat, Amita McPhillips, Lisa N. Marcu, Laura Saif Islam, M. Electrical and Computer Engineering Department University of California DavisCA95616 United States Biomedical Engineering Department University of California DavisCA95616 United States

ISBN: (纸本)9781510669659

Fluorescence Lifetime Imaging (FLIM) is a powerful technique that measures the decay time of fluorophores present in tissue samples alluding to their constituent molecules. FLIM has gained popularity in biomedical imaging for applications such as detecting cancerous tumors, surgical guidance, etc. However, conventional FLIM systems are limited by a reduced number of spectral bands and long acquisition time. Moreover, the large footprint, complexity, and cost of the instrumentation make it difficult for clinical applications. In this paper, we demonstrate a reconstruction-based hyperspectral detector that can resolve decay time and intensities in broad spectral ranges while providing high sensitivity, high gain, and fast response time. The hyperspectral detector is comprised of an array of efficient, ultrafast avalanche photodetectors integrated with nanophotonic structures. We utilize different nanostructures in the detectors to modulate light-matter interactions in spectral channels. This allows us to computationally reconstruct the spectral profile of the incoming fluorescence spectrum without the need for additional filters or dispersive optics. Also, the nanophotonic structures enhance efficiency (by a factor of 2 to 10 over different wavelengths) while providing fast response time. An innovative detector design has been employed to reduce the breakdown of the avalanche photodetectors to-7.8V while maintaining high gain (∼50) across the spectral range. Therefore, enabling low light detection with a high signal-To-noise ratio for FLIM applications. Added spectral channels would provide valuable information about tissue materials, morphology, and disease diagnosis. Such innovative hyperspectral sensors can now be integrated on-chip capable of miniaturizing the FLIM system and making it a commercially viable tool for clinical use. This technology has the potential to revolutionize the current FLIM system with improved detection capabilities opening doors for new ho

关键词： Hyperspectral imaging

来源：评论

学校读者我要写书评

暂无评论

Exploring the trade-off between deep-learning and explainable models for brain-machine interfaces 38

Exploring the trade-off between deep-learning and explainabl...

引用

38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Cubillos, Luis H. Revach, Guy Mender, Matthew J. Costello, Joseph T. Temmar, Hisham Hite, Aren Zutshi, Diksha Wallace, Dylan M. Ni, Xiaoyong Kelberman, Madison M. Willsey, Matthew S. van Sloun, Ruud J.G. Shlezinger, Nir Patil, Parag Draelos, Anne Chestek, Cynthia A. Departments of Electrical & Computer Engineering Biomedical Engineering Robotics Computational Medicine & Bioinformatics and Neurosurgery University of Michigan United States Biointerfaces Institute Neuroscience Institute University of Michigan United States Department of Information Technology and Electrical Engineering ETH Zürich Switzerland Department of Electrical Engineering Eindhoven University of Technology Netherlands School of Electrical and Computer Engineering Ben-Gurion University Israel

People with brain or spinal cord-related paralysis often need to rely on others for basic tasks, limiting their independence. A potential solution is brain-machine interfaces (BMIs), which could allow them to voluntarily control external devices (e.g., robotic arm) by decoding brain activity to movement commands. In the past decade, deep-learning decoders have achieved state-of-the-art results in most BMI applications, ranging from speech production to finger control. However, the'black-box' nature of deep-learning decoders could lead to unexpected behaviors, resulting in major safety concerns in real-world physical control scenarios. In these applications, explainable but lower-performing decoders, such as the Kalman filter (KF), remain the norm. In this study, we designed a BMI decoder based on KalmanNet, an extension of the KF that augments its operation with recurrent neural networks to compute the Kalman gain. This results in a varying "trust" that shifts between inputs and dynamics. We used this algorithm to predict finger movements from the brain activity of two monkeys. We compared KalmanNet results offline (pre-recorded data, n = 13 days) and online (real-time predictions, n = 5 days) with a simple KF and two recent deep-learning algorithms: tcFNN (non-ReFIT version) and LSTM. KalmanNet achieved comparable or better results than other deep learning models in offline and online modes, relying on the dynamical model for stopping while depending more on neural inputs for initiating movements. We further validated this mechanism by implementing a heteroscedastic KF that used the same strategy, and it also approached state-of-the-art performance while remaining in the explainable domain of standard KFs. However, we also see two downsides to KalmanNet. KalmanNet shares the limited generalization ability of existing deep-learning decoders, and its usage of the KF as an inductive bias limits its performance in the presence of unseen noise distributions. Despite thi

关键词：

来源：评论

学校读者我要写书评

暂无评论

Alzheimer Disease Detection Studies: Perspective on Multi-Modal Data

引用

Yearbook of Medical Informatics 2025年第1期33卷 266-276页

作者： Dehghani, Farzaneh Derafshi, Reihaneh Lin, Joanna Bayat, Sayeh Bento, Mariana Biomedical Engineering Department University of Calgary Canada Computer Science Department University of Calgary Canada Geomatics Engineering Department University of Calgary Canada Hotchkiss Brain Institute Cumming School of Medicine University of Calgary Canada Electrical and Software Engineering Department University of Calgary Canada

OBJECTIVES: Alzheimer's Disease (AD) is one of the most common neurodegenerative diseases, resulting in progressive cognitive decline, and so accurate and timely AD diagnosis is of critical importance. To this end, various medical technologies and computer-aided diagnosis (CAD), ranging from biosensors and raw signals to medical imaging, have been used to provide information about the state of AD. In this survey, we aim to provide a review on CAD systems for automated AD detection, focusing on different data types: namely, signals and sensors, medical imaging, and electronic medical records (EMR). METHODS: We explored the literature on automated AD detection from 2022-2023. Specifically, we focused on various data resources and reviewed several preprocessing and learning methodologies applied to each data type, as well as evaluation metrics for model performance evaluation. Further, we focused on challenges, future perspectives, and recommendations regarding automated AD diagnosis. RESULTS: Compared to other modalities, medical imaging was the most common data type. The prominent modality was Magnetic Resonance Imaging (MRI). In contrast, studies based on EMR data type were marginal because EMR is mostly used for AD prediction rather than detection. Several challenges were identified: data scarcity and bias, imbalanced datasets, missing information, anonymization, lack of standardization, and explainability. CONCLUSION: Despite recent developments in automated AD detection, improving the trustworthiness and performance of these models, and combining different data types will improve usability and reliability of CAD tools for early AD detection in the clinical practice. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://***/licenses/by/4.0/).

关键词： Alzheimer’s Disease computer-aided Diagnosis Electronic Medical Records Medical Imaging Signals and Sensors

来源：评论

学校读者我要写书评

暂无评论

High-Throughput Independent Component Analysis Processor for Full Duplex Systems

引用

IEEE Journal on Selected Areas in Communications 2023年第9期41卷 2821-2832页

作者： Cheng, Jen-Hao Chang, Tien-Min Shen, Chung-An Fouda, Mohammed E. Eltawil, Ahmed M. National Taiwan University of Science and Technology Department of Electronic and Computer Engineering Taipei10607 Taiwan University of California at Irvine Electrical Engineering and Computer Science Department IrvineCA92697 United States King Abdullah University of Science and Technology Electrical and Computer Engineering Program Thuwal23955 Saudi Arabia

This paper presents the algorithm and very-large-scale integration (VLSI) architecture of a high-throughput and highly efficient independent component analysis (ICA) processor for self-interference cancellation (SIC) in in-band full-duplex (IBFD) systems. This is the first VLSI architecture reported in the literature based on the state-of-the-art entropy bound minimization (EBM) approach. A novel ICA algorithm is presented in this paper with momentum gradient descent optimization. Simulation results show that the number of iterations for the proposed algorithm is significantly reduced compared to the conventional ICA algorithms. Furthermore, a novel early-distribution estimation scheme is proposed in the designed ICA processor to compute multiple distribution functions with low latency and low complexity. The processing flow and the efficiency for the hardware utilization are specifically designed so that the processing speed is maximized with minimum employment of hardware components. The proposed ICA processor is designed and implemented based on the application-specific-integrated circuit (ASIC) flow. The post-layout estimations show that compared with the conventional EBM-based scheme, the proposed design improves the throughput and efficiency by 30x. In addition, compared to prior designs shown in the literature, the proposed ICA processor also demonstrates a significant enhancement in terms of throughput and efficiency. © 1983-2012 IEEE.

关键词： VLSI circuits

来源：评论

学校读者我要写书评

暂无评论

Crafting chirality in three dimensions via a novel fabrication technique for bound states in the continuum metasurfaces

引用

Light(Science & Applications) 2024年第3期13卷 390-392页

作者： Zaid Haddadin Anna My Nguyen Lisa V.Poulikakos Department of Electrical&Computer Engineering University of California San DiegoLa JollaCAUSA Department of Mechanical&Aerospace Engineering University of California San DiegoLa JollaCAUSA Program of Materials Science&Engineering University of California San DiegoLa JollaCAUSA

An additional deposition step was added to a multi-step electron beam lithographic fabrication process to unlock the height dimension as an accessible parameter for resonators comprising unit cells of quasi-bound stat... 详细信息

关键词： dimensions dimension intrinsic

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：