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Spinal functional Magnetic Resonance Imaging (fMRI) on Human Studies: A Literature Review

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Spinal functional Magnetic Resonance Imaging (fMRI) on Human...

2019 Advances in science and engineering Technology International Conferences, ASET 2019

作者： Al-Momani, Sajedah Dhou, Salam Biomedical Engineering Graduate Program American University of Sharjah Sharjah United Arab Emirates Department of Computer Science and Engineering Biomedical Engineering Graduate Program Biosciences and Bioengineering Research Institute American University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9781538682715

Spinal functional Magnetic Resonance Imaging (fMRI) is a newly emerging non-invasive imaging technique that has been introduced to study the Blood Oxygenation Level Dependent (BOLD) changes in the spinal cord associated with a certain activity or even at rest. Spinal fMRI is also used to assess the treatment of many dysfunctions affect the spinal cord such as spinal cord injury (SCI) and Multiple sclerosis (MS). The purpose of this paper is to propose a literature review of spinal fMRI studies performed on healthy human volunteers. The studies reviewed are divided based on the paradigm being performed during image acquisition into (1) studies under activities and stimulus which are further classified according to the type of the stimuli, and (2) studies at resting state. Moreover, the limitations of spinal fMRI and how to tackle them are discussed. © 2019 IEEE.

关键词： Magnetic resonance imaging

MICROBUNDLECOMPUTE: AUTOMATED SEGMENTATION, TRACKING, AND ANALYSIS OF SUBDOMAIN DEFORMATION IN CARDIAC MICROBUNDLES

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arXiv 2023年

作者： Kobeissi, Hiba Jilberto, Javiera Karakan, M. Çağatay Gao, Xining DePalma, Samuel J. Das, Shoshana L. Quach, Lani Urquia, Jonathan Baker, Brendon M. Chen, Christopher S. Nordsletten, David Lejeune, Emma Department of Mechanical Engineering Boston University BostonMA02215 United States Center for Multiscale and Translational Mechanobiology Boston University BostonMA02215 United States Department of Biomedical Engineering University of Michigan Ann ArborMI48109 United States Photonics Center Boston University BostonMA02215 United States Department of Biomedical Engineering Boston University BostonMA02215 United States Harvard-MIT Program in Health Sciences and Technology Institute for Medical Engineering and Science Massachusetts Institute of Technology CambridgeMA02139 United States Wyss Institute for Biologically Inspired Engineering Harvard University BostonMA02215 United States Department of Electrical and Computer Engineering New York Institute of Technology New YorkNY10023 United States Department of Cardiac Surgery University of Michigan MI48109 United States Department of Biomedical Engineering School of Imaging Sciences and Biomedical Engineering King’s College London King’s Health Partners LondonSE1 7EH United Kingdom

Advancing human induced pluripotent stem cell derived cardiomyocyte (hiPSC-CM) technology will lead to significant progress ranging from disease modeling, to drug discovery, to regenerative tissue engineering. Yet, alongside these potential opportunities comes a critical challenge: attaining mature hiPSC-CM tissues. At present, there are multiple techniques to promote maturity of hiPSC-CMs including physical platforms and cell culture protocols. However, when it comes to making quantitative comparisons of functional behavior, there are limited options for reliably and reproducibly computing functional metrics that are suitable for direct cross-system comparison. In addition, the current standard functional metrics obtained from time-lapse images of cardiac microbundle contraction reported in the field (i.e., post forces, average tissue stress) do not take full advantage of the available information present in these data (i.e., full-field tissue displacements and strains). Thus, we present "MicroBundleCompute, " a computational framework for automatic quantification of morphology-based mechanical metrics from movies of cardiac microbundles. Briefly, this computational framework offers tools for automatic tissue segmentation, tracking, and analysis of brightfield and phase contrast movies of beating cardiac microbundles. It is straightforward to implement, runs without user intervention, requires minimal input parameter setting selection, and is computationally inexpensive. In this paper, we describe the methods underlying this computational framework, show the results of our extensive validation studies, and demonstrate the utility of exploring heterogeneous tissue deformations and strains as functional metrics. With this manuscript, we disseminate "MicroBundleCompute" as an open-source computational tool with the aim of making automated quantitative analysis of beating cardiac microbundles more accessible to the *** Codes 92F05, 74A05 © 2023, CC BY-SA.

关键词： Cell culture

An Exploration of Active Learning for Affective Digital Phenotyping

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arXiv 2022年

作者： Washington, Peter Mutlu, Cezmi Kline, Aaron Hou, Cathy Dunlap, Kaitlyn Kent, Jack Husic, Arman Stockham, Nate Chrisman, Brianna Paskov, Kelley Jung, Jae-Yoon Wall, Dennis P. Department of Bioengineering Stanford University 443 Via Ortega StanfordCA94305 United States Stanford University 1265 Welch Rd StanfordCA94305 United States Department of Computer Science Stanford University 353 Jane Stanford Way StanfordCA94305 United States Department of Electrical Engineering Stanford University 350 Jane Stanford Way StanfordCA94305 United States Department of Neuroscience Stanford University 213 Quarry Rd StanfordCA94305 United States Department of Biomedical Data Science Stanford University 1265 Welch Rd StanfordCA94305 United States

Some of the most severe bottlenecks preventing widespread development of machine learning models for human behavior include a dearth of labeled training data and difficulty of acquiring high quality labels. Active learning is a paradigm for using algorithms to computationally select a useful subset of data points to label using metrics for model uncertainty and data similarity. We explore active learning for naturalistic computer vision emotion data, a particularly heterogeneous and complex data space due to inherently subjective labels. Using frames collected from gameplay acquired from a therapeutic smartphone game for children with autism, we run a simulation of active learning using gameplay prompts as metadata to aid in the active learning process. We find that active learning using information generated during gameplay slightly outperforms random selection of the same number of labeled frames. We next investigate a method to conduct active learning with subjective data, such as in affective computing, and where multiple crowdsourced labels can be acquired for each image. Using the Child Affective Facial Expression (CAFE) dataset, we simulate an active learning process for crowdsourcing many labels and find that prioritizing frames using the entropy of the crowdsourced label distribution results in lower categorical cross-entropy loss compared to random frame selection. Collectively, these results demonstrate pilot evaluations of two novel active learning approaches for subjective affective data collected in noisy settings. © 2022, CC BY.

关键词： Crowdsourcing

Review of Image-Guided Percutaneous Coronary Interventions

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Review of Image-Guided Percutaneous Coronary Interventions

2019 Advances in science and engineering Technology International Conferences, ASET 2019

作者： Alatoom, Aseel Farhat, Jumana Dhou, Salam Biomedical Engineering Graduate Program American University of Sharjah Sharjah United Arab Emirates Department of Computer Science and Engineering Biomedical Engineering Graduate Program Biosciences and Bioengineering Research Institute American University of Sharjah Sharjah United Arab Emirates

ISBN: (纸本)9781538682715

Image-guided surgery (IGS) involves using surgical instruments tracking system to guide the surgeon during invasive surgical procedures. The use of preoperative or intraoperative images is very essential in providing navigation for different medical applications. In this paper, a literature review of different imaging modalities that aid in the diagnosis and treatment of coronary artery disease (CAD) is proposed. The imaging modalities discussed include x-ray fluoroscopy, coronary computed tomography angiography (CCTA), fractional flow reserve (FFR), cardiac single-photon emission computed tomography (SPECT), cardiovascular magnetic resonance imaging (CMRI) and ultrasound. Additionally, pseudoaneurysms, which can result from percutaneous coronary interventions (PCI) procedure, are reviewed as well as the treatment procedure. Finally, a comparison between the different imaging modalities is carried out, based on the number of papers that have been published, in addition to the sensitivity and specificity for each modality according to PubMed and Web of science databases. © 2019 IEEE.

关键词： Ultrasonics

ON-OFF Neuromorphic ISING Machines using Fowler-Nordheim Annealers

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arXiv 2024年

作者： Chen, Zihao Xiao, Zhili Akl, Mahmoud Leugring, Johannes Olajide, Omowuyi Malik, Adil Dennler, Nik Harper, Chad Bose, Subhankar Gonzalez, Hector A. Eshraghian, Jason Pignari, Riccardo Urgese, Gianvito Andreou, Andreas G. Shankar, Sadasivan Mayr, Christian Cauwenberghs, Gert Chakrabartty, Shantanu Department of Electrical and Systems Engineering Washington University in St. Louis One Brookings Drive St. LouisMO63130 United States Department of Bioengineering University of California 9500 Gilman Dr La Jolla San DiegoCA92093 United States SpiNNcloud Systems GmbH Freibergerstr. 37 Dresden01067 Germany Department of Electrical and computer engineering Johns Hopkins University 3400 N. Charles Street BaltimoreMD21218 United States SLAC National Accelerator Laboratory 2575 Sand Hill Road Menlo ParkCA94025 United States Department of Electrical and Electronic Engineering Imperial College London Exhibition Rd LondonSW7 2AZ United Kingdom International Centre for Neuromorphic Engineering Western Sydney University Penrith Second Ave KingswoodNSW2747 Australia Department of Physics University of California Berkeley University Avenue and Oxford St BerkeleyCA94720 United States Department of Electrical and Computer Engineering University of California Santa Cruz 1156 High Street Santa CruzCA95064 United States Politecnico di Torino Address: Corso Duca degli Abruzzi 24 Torino10129 Italy Redwood Center for Theoretical Neuroscience Helen Wills Neuroscience Institute University of California Berkeley University Avenue and Oxford St BerkeleyCA94720 United States Biocomputation Group University of Hertfordshire Exhibition Rd LondonSW7 2AZ United Kingdom Materials Science and Engineering Stanford University 450 Jane Stanford Way StanfordCA94305 United States Highly-Parallel VLSI-Systems and Neuro-Microelectronics Technische Universität Dresden Mommsenstraße 12 Dresden01069 Germany Scads.AI: Center for scalable data analytics and artificial intelligence Strehlener Street 12 14 Dresden01069 Germany

We introduce NeuroSA, a neuromorphic architecture specifically designed to ensure asymptotic convergence to the ground state of an Ising problem using an annealing process that is governed by the physics of quantum mechanical tunneling using Fowler-Nordheim (FN). The core component of NeuroSA consists of a pair of asynchronous ON-OFF neurons, which effectively map classical simulated annealing (SA) dynamics onto a network of integrate-and-fire (IF) neurons. The threshold of each ON-OFF neuron pair is adaptively adjusted by an FN annealer which replicates the optimal escape mechanism and convergence of SA, particularly at low temperatures. To validate the effectiveness of our neuromorphic Ising machine, we systematically solved various benchmark MAX-CUT combinatorial optimization problems. Across multiple runs, NeuroSA consistently generates solutions that approach the state-of-the-art level with high accuracy (greater than 99%), and without any graph-specific hyperparameter tuning. For practical illustration, we present results from an implementation of NeuroSA on the SpiNNaker2 platform, highlighting the feasibility of mapping our proposed architecture onto a standard neuromorphic accelerator platform. © 2024, CC BY-NC-SA.

关键词： Simulated annealing

From Nano to Macro: Overview of the IEEE Bio Image and Signal Processing Technical Committee

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arXiv 2022年

作者： Aviyente, Selin Frangi, Alejandro Meijering, Erik Muñoz-Barrutia, Arrate Liebling, Michael De Ville, Dimitri Van Olivo-Marin, Jean-Christophe Kovačević, Jelena Unser, Michael The Department of Electrical and Computer Engineering Michigan State University East LansingMI48824 United States Schools of Computing and Medicine University of Leeds LeedsLS2 9JT United Kingdom The Alan Turing Institute London United Kingdom and Cardiovascular Sciences KU Leuven Leuven Belgium The School of Computer Science and Engineering University of New South Wales SydneyNSW2052 Australia The Bioengineering Department Universidad Carlos III de Madrid Madrid Leganés Spain The Idiap Research Institute Martigny Switzerland The Neuro-X Institute School of Engineering EPFL Geneva Faculty of Medicine University of Geneva Switzerland The Cell Biology and Infection Department Institut Pasteur Paris France The New York University Tandon School of Engineering BrooklynNY United States The School of Engineering EPFL Lausanne Switzerland

The Bio Image and Signal Processing (BISP) Technical Committee (TC) of the IEEE Signal Processing Society (SPS) promotes activities within the broad technical field of biomedical image and signal processing. Areas of interest include medical and biological imaging, digital pathology, molecular imaging, microscopy, and associated computational imaging, image analysis, and image-guided treatment, alongside physiological signal processing, computational biology, and bioinformatics. BISP has 40 members and covers a wide range of EDICS, including CIS-MI: Medical Imaging, BIO-MIA: Medical Image Analysis, BIO-BI: Biological Imaging, BIO: Biomedical Signal Processing, BIO-BCI: Brain/Human-computer Interfaces, and BIO-INFR: Bioinformatics. BISP plays a central role in the organization of the IEEE International Symposium on Biomedical Imaging (ISBI) and contributes to the technical sessions at the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), and the IEEE International Conference on Image Processing (ICIP). In this paper, we provide a brief history of the TC, review the technological and methodological contributions its community delivered, and highlight promising new directions we anticipate. © 2022, CC BY.

关键词： Bioinformatics

Thermalization of fluorescent protein exciton-polaritons at room temperature

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arXiv 2022年

作者： Satapathy, Sitakanta Liu, Bin Deshmukh, Prathmesh Molinaro, Paul M. Dirnberger, Florian Khatoniar, Mandeep Koder, Ronald L. Menon, Vinod M. Department of Physics Center for Discovery and Innovation The City College of New York 85 St. Nicholas Terrace New YorkNY10031 United States The PhD Program in Physics The Graduate Center of the City University of New York 365 5th Ave New YorkNY10016 United States Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States

Fluorescent proteins (FPs) have recently emerged as a serious contender for realizing ultra-low threshold room temperature exciton-polariton condensation and lasing. Our contribution investigates the thermalization of FP microcavity exciton-polaritons upon optical pumping under ambient conditions. We realize polariton cooling using a new FP molecule, called mScarlet, coupled strongly to the optical modes in a Fabry-Pérot cavity. Interestingly, at the threshold excitation energy (fluence) of ~9 nJ/pulse (15.6 mJ/cm2), we observe an effective temperature, Teff ~350 ± 35 K close to the lattice temperature indicative of strongly thermalized exciton-polaritons at equilibrium. This efficient thermalization results from the interplay of radiative pumping facilitated by the energetics of the lower polariton branch and the cavity Qfactor. Direct evidence for dramatic switching from an equilibrium state into a metastable state is observed for the organic cavity polariton device at room temperature via deviation from the Maxwell-Boltzmann statistics at k1 = 0 above the threshold. Thermalized polariton gases in organic systems at equilibrium hold substantial promise for designing room temperature polaritonic circuits, switches, and lattices for analog simulation. © 2022, CC BY-NC-SA.

关键词： Polariton

Quantitative particle agglutination assay for point-of-care testing using mobile holographic imaging and deep learning

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arXiv 2021年

作者： Luo, Yi Joung, Hyou-Arm Esparza, Sarah Rao, Jingyou Garner, Omai Ozcan, Aydogan Electrical & Computer Engineering Department University of California Los AngelesCA90095 United States University of California Los AngelesCA90095 United States Bioengineering Department University of California Los AngelesCA90095 United States Computer Science Department University of California Los AngelesCA90095 United States Department of Pathology and Laboratory Medicine University of California Los AngelesCA90095 United States

Particle agglutination assays are widely adapted immunological tests that are based on antigen-antibody interactions. Antibody-coated microscopic particles are mixed with a test sample that potentially contains the target antigen, as a result of which the particles form clusters, with a size that is a function of the antigen concentration and the reaction time. Here, we present a quantitative particle agglutination assay that combines mobile lens-free microscopy and deep learning for rapidly measuring the concentration of a target analyte;as its proof-of-concept, we demonstrate high-sensitivity C-reactive protein (hs-CRP) testing using human serum samples. A dual-channel capillary lateral flow device is designed to host the agglutination reaction using 4 μL of serum sample with a material cost of 1.79 cents per test. A mobile lens-free microscope records time-lapsed inline holograms of the lateral flow device, monitoring the agglutination process over 3 min. These captured holograms are processed, and at each frame the number and area of the particle clusters are automatically extracted and fed into shallow neural networks to predict the CRP concentration. 189 measurements using 88 unique patient serum samples were utilized to train, validate and blindly test our platform, which matched the corresponding ground truth concentrations in the hs-CRP range (0-10μg/mL) with an R2value of 0.912. This computational sensing platform was also able to successfully differentiate very high CRP concentrations (e.g., >10-500 μg/mL) from the hs-CRP range. This mobile, cost-effective and quantitative particle agglutination assay can be useful for various point-of-care sensing needs and global health related applications. Copyright © 2021, The Authors. All rights reserved.

关键词： Antigen-antibody reactions

In vivo imaging with a flat, lensless microscope

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Research Square

Research Square 2021年

作者： Adams, Jesse K. Yan, Dong Wu, Jimin Boominathan, Vivek Gao, Sibo Rodriguez, Alex V. Carns, Jennifer Richards-Kortum, Rebecca Kemere, Caleb Veeraraghavan, Ashok Robinson, Jacob T. Applied Physics Program Rice University 6100 Main Street HoustonTX77005 United States Department of Electrical and Computer Engineering Rice University 6100 Main Street HoustonTX77005 United States Department of Neuroscience Baylor College of Medicine One Baylor Plaza HoustonTX77030 United States Department of Bioengineering Rice University 6100 Main Street HoustonTX77005 United States Department of Computer Science Rice University 6100 Main Street HoustonTX77005 United States

Lenless microscopes that form images using simple, compact optics, along with associated computational algorithms provide several advantages: small, inexpensive form factors, large fields of view (FOV), and the ability to refocus an image after capture. To date, however, lensless microscopy has yet to be demonstrated for in vivo biological imaging. The primary challenge with in vivo bio-imaging is these dense, low-contrast scenes cannot be accurately reconstructed with existing lensless techniques. To overcome this challenge, we designed an optical phase mask that creates a point-spread function consisting of high-contrast contours with a broad spatial frequency spectrum. Here we show that this "contour" phase mask enables in vivo imaging where previous lensless imaging technologies have failed. As a proof of concept, we demonstrate 3D imaging of a behaving invertebrate, functional calcium imaging in mouse cortex, and in vivo imaging of microvasculature in the human oral mucosa. Together these results demonstrate the ability of lensless imaging to operate in realistic biological imaging applications ranging from pre-clinical animal models to clinical biomedical imaging. Overall, this "Bio-FlatScope" is a clinically relevant imaging technique with advantages of 3D computational refocusing in a low-cost, small form factor that is useful for low-resource settings and difficult-to-reach areas of the body. © 2021, CC BY.

关键词： Microscopes