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arXiv 2024年

作者： Khawaled, Samah Freiman, Moti The Interdisciplinary program in Applied Mathematics Faculty of Mathematics Technion Israel Institute of Technology Israel The Faculty of Biomedical Engineering Technion Israel Institute of Technology Israel

The ability to reconstruct high-quality images from undersampled MRI data is vital in improving MRI temporal resolution and reducing acquisition times. Deep learning methods have been proposed for this task, but the lack of verified methods to quantify the uncertainty in the reconstructed images hampered clinical applicability. We introduce "NPB-REC", a non-parametric fully Bayesian framework, for MRI reconstruction from undersampled data with uncertainty estimation. We use Stochastic Gradient Langevin Dynamics during training to characterize the posterior distribution of the network parameters. This enables us to both improve the quality of the reconstructed images and quantify the uncertainty in the reconstructed images. We demonstrate the efficacy of our approach on a multi-coil MRI dataset from the fastMRI challenge and compare it to the baseline End-to-End Variational Network (E2E-VarNet). Our approach outperforms the baseline in terms of reconstruction accuracy by means of PSNR and SSIM (34.55, 0.908 vs. 33.08, 0.897, p Copyright © 2024, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Evaluating Crosslinking Efficiency and Cytocompatibility of Three Commonly Used Photoinitiators Across Different Cell-Compatible Hydrogel Platforms

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SSRN 2025年

作者： Gavish Moscovitz, Aya Simaan Yameen, Haneen Bar-Am, Orit Seliktar, Dror The Faculty of Biomedical Engineering Technion-Israel Institute of Technology Haifa Israel The Interdisciplinary Program in Biotechnology Technion–Israel Institute of Technology Haifa Israel

biomedical hydrogels that undergo a rapid liquid-to-solid phase transition often use a photopolymerization strategy to crosslink the polymer network. In applications such as 3D bioprinting or tissue engineering that involve cell-laden hydrogels, or where in-vivo polymerization is desired (i.e., in-situ), cytotoxicity of the hydrogel crosslinking reaction becomes an important issue. There are only a few cytocompatible photoinitiators (PIs) that are commonly used for crosslinking biomedical hydrogels, including Irgacure2959 (I2959), lithium phenyl-2,4,6-trimethylbenzoylphosphinate (LAP) and EosinY (EY). These PIs are illuminated at 365nm, 405nm and 525nm, respectively. The photopolymerization conditions, including PI concentration and illumination intensity may affect both the cytotoxicity of the reaction and the crosslinking of the hydrogel. Herein we tested these three PIs to optimize the maximum crosslinking efficiency while minimizing cell death associated with the photochemical reaction. Testing was performed on three different types of cell-compatible hydrogels used for cell encapsulation and 3D cell growth, including a synthetic material (poly(ethylene glycol)-diacrylate, PEG-DA), a semi-synthetic material (PEG-fibrinogen, PF) and a modified biological material (methacrylated fibrinogen, FibMA). Strain-rate controlled rheology was used to characterize the crosslinking reaction efficiency, both in terms of maximum shear storage modulus, G’, and crosslinking kinetics. Viability was examined on human dermal fibroblasts in 3D culture within photopolymerized PF hydrogels crosslinked using each of the PIs. The results showed that PI concentration and the illumination intensity had significant impact on the crosslinking efficiency, with each material system demonstrating different responses to the PI parameters. Optimal photo-crosslinking conditions, considering both crosslinking efficiency and cell viability were not the same for the modified protein hydrogels, as co

关键词： Cell death

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A novel methodology based on static visual stimuli and kinesthetic motor imagery for upper limb neurorehabilitation

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Research on biomedical engineering 2024年第3-4期40卷 687-700页

作者： Bastos-Filho, T.F. Villa-Parra, A.C. Guerrero-Méndez, C.D. González-Cely, A.X. Blanco-Díaz, C.F. Delisle-Rodríguez, D. Igasaki, T. Vitoria Brazil Biomedical Engineering Research Group Salesian Polytechnic University Cuenca Ecuador Postgraduate Program in Neuroengineering Edmond and Lily Safra International Institute of Neurosciences Santos Dumont Institute Macaiba Brazil Faculty of Advanced Science and Technology Kumamoto University Kumamoto Japan

Purpose: This work proposes a protocol to be used in a Brain-Computer Interface (BCI) for hand and finger movement rehabilitation aimed at post-stroke patients. This strategy is based on Electroencephalography (EEG) and uses concepts of both Static Visual Stimuli (SVS) of the own subject’s hand (OwnSVS) and Kinesthetic Motor Imagery (KMI) to improve the motor task recognition of the same limb. Methods: The protocol proposed here takes into account several aspects, such as physical rehabilitation strategies, Active Hand Orthosis (AHO) — represented by a robotic glove —, and the acquisition of the EEG signal over the brain motor area. Power Spectral Density (PSD) and Riemannian Geometry (RG) are used for feature extraction in this work, considering Mu (μ, 8–12 Hz), Low-Beta (Low-β, 13–17 Hz) and High-Beta (High-β, 18–24 Hz) frequency bands. Moreover, a feature selection stage using Pair-Wise Feature Proximity (PWFP) is also used before input to a Machine Learning (ML) classifier. Here, Linear Discriminant Analysis (LDA), Support Vector Machine (SVM), k-Nearest Neighbors (kNN), and Decision Tree (DT) are compared. Results: As results, evaluated in 10 healthy subjects, features using PSD-PWFP and kNN achieved a maximum ACC of 89.81% (with AHO movements), improving by 3% the standard protocol (without AHO movements). Conclusions: The findings of this work indicate that AHO movement assistance can improve the recognition of hand opening and closing MI tasks, which can be implemented in the design of robotic BCI controllers for hand and finger movement neurorehabilitation in stroke patients. © The Author(s), under exclusive licence to The Brazilian Society of biomedical engineering 2024.

关键词： Electroencephalography

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Multilabel Classification of Intracranial Hemorrhages Using Deep Learning and Preprocessing Techniques on Non-contrast CT Images 27th

Multilabel Classification of Intracranial Hemorrhages Using...

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27th Iberoamerican Congress on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications, CIARP 2024

作者： Salas, Rodrigo Castro, Juan Sebastian Querales, Marvin Saavedra, Carolina Prieto, Claudia Chabert, Steren Biomedical Engineering School Engineering Faculty Universidad de Valparaíso General Cruz 222 Valparaíso Chile Center of Interdisciplinary Biomedical and Engineering Research for Health - MEDING Universidad de Valparaíso Valparaíso Chile Santiago Chile Medical Technology School Medicine Faculty Universidad de Valparaíso Viña del Mar Chile Departamento de Informática Universidad Técnica Federico Santa María Valparaíso Chile Engineering School Pontificia Universidad Católica de Chile Santiago Chile Department of Biomedical Engineering King’s College London London United Kingdom

ISBN: (纸本)9783031766039

This study presents a comprehensive framework that integrates a deep learning model with advanced image preprocessing techniques to improve the multilabel classification of five types of intracranial hemorrhage—epidural, intraparenchymal, intraventricular, subarachnoid, and subdural—using non-contrast computed tomography (CT) images. The framework includes strategies to mitigate overfitting, data augmentation, and a custom loss function. It was rigorously evaluated on a dataset of over 25,000 non-contrast CT scans, each labeled by expert radiologists across six classes. The proposed model achieved 99% accuracy and 92.1% sensitivity in detecting intracranial hemorrhage, outperforming previously reported methods. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Contrastive Learning

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VR-Based Implicit Authentication Using Electromyogram and Inertial Measurement Unit 23

VR-Based Implicit Authentication Using Electromyogram and In...

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23rd International Conference on Cyberworlds, CW 2024

作者： Yu, Da-Young Lee, Hyung-Tak Kim, Youngsam Roh, Jong-Hyuk Kim, Soohyung Ku, Jeonghun Hwang, Han-Jeong Korea University Interdisciplinary Graduate Program for Artificial Intelligence Smart Convergence Technology Dept. Electronics and Information Engineering Sejong Korea Republic of Korea University Dept. Electronics and Information Engineering Sejong Korea Republic of Daejeon Korea Republic of Keimyung University College of Medicine Department of Biomedical Engineering Daegu Korea Republic of

ISBN: (纸本)9798331527174

Biometrics based on electromyogram (EMG) and inertial measurement unit (IMU) signals has received significant attention due to its resistance to forgery and tampering, as well as its relatively higher convenience and security compared to other biometric modalities. However, most EMG and IMU signal-based authentication methods require explicit authentication using unnatural gestures, which is not userfriendly. To address this, we collected EMG and IMU data during virtual reality (VR) rhythm game play, which does not require explicit gestures, and performed implicit authentication. Using a linear discriminant analysis (LDA) classifier, we achieved classification accuracies of 91.71% for human identification and 87.91% for human authentication. The result demonstrated the feasibility of a seamless and implicit authentication in VR environments. © 2024 IEEE.

关键词： Electromyography

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mRNA vaccines: Past, present, future

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Asian Journal of Pharmaceutical Sciences 2022年第4期17卷 491-522页

作者： Mia Karam Georges Daoud Biomedical Engineering Program Maroun Semaan Faculty of Engineering and ArchitectureBeirut 11072020Lebanon Department of Biochemistry and Molecular Genetics Faculty of MedicineBeirut 11072020Lebanon Department of Anatomy Cell Biologyand Physiological SciencesFaculty of MedicineAmerican University of BeirutBeirut 11072020Lebanon

mRNA vaccines have emerged as promising alternative platforms to conventional *** ease of production,low cost,safety profile and high potency render them ideal candidates for prevention and treatment of infectious diseases,especially in the midst of *** challenges that face in vitro transcribed RNA were partially amended by addition of tethered adjuvants or co-delivery of naked mRNA with an adjuvanttethered ***,it wasn’t until recently that the progress made in nanotechnology helped enhance mRNA stability and delivery by entrapment in novel delivery systems of which,lipid *** continuous advancement in the fields of nanotechnology and tissue engineering provided novel carriers for mRNA vaccines such as polymeric nanoparticles and *** studies have shown the advantages of adopting mRNA vaccines for viral diseases and cancer in animal and human ***-amplifying mRNA is considered today the next generation of mRNA vaccines and current studies reveal promising *** review provides a comprehensive overview of mRNA vaccines used in past and present studies,and discusses future directions and challenges in advancing this vaccine platform to widespread clinical use.

关键词： mRNA vaccine Virus Cancer Nanoparticles COVID-19

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Development of exosome membrane materialsfused microbubbles for enhanced stability and efficient drug delivery of ultrasound contrast agent

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Acta Pharmaceutica Sinica B 2023年第12期13卷 4983-4998页

作者： Yongho Jang Jeehun Park Pilsu Kim Eun-Joo Park Hyungjin Sun Yujin Baek Jaehun Jung Tai-kyong Song Junsang Doh Hyuncheol Kim Department of Chemical and Biomolecular Engineering Sogang UniversitySeoul 04107Republic of Korea Research Institute of Advanced Materials(RIAM) Institute of Engineering ResearchSeoul National UniversitySeoul 08826Republic of Korea Department of Electronic Engineering Sogang UniversitySeoul 04107Republic of Korea Biomedical Research Institute&Department of Radiology Seoul National University HospitalSeoul 03080Republic of Korea Interdisciplinary Program in Bioengineering Seoul National UniversitySeoul 08826Republic of Korea Department of Materials Science and Engineering Seoul National UniversitySeoul 08826Republic of Korea Institute of Engineering Research Bio-MAX InstituteSeoul National UniversitySeoul 08826Republic of Korea Department of Biomedical Engineering Sogang UniversitySeoul 04107Republic of Korea

Lipid-coated microbubbles are widely used as an ultrasound contrast agent,as well as drug delivery ***,the two main limitations in ultrasound diagnosis and drug delivery using microbubbles are the short half-life in the blood system,and the difficulty of surface modification of microbubbles for active *** exosome,a type of extracellular vesicle,has a preferentially targeting ability for its original *** this study,exosome-fused microbubbles(Exo-MBs)were developed by embedding the exosome membrane proteins into *** a result,the stability of Exo-MBs is improved over the conventional *** the same principle that under the exposure of ultrasound,microbubbles are cavitated and self-assembled into nano-sized particles,and Exo-MBs are self-assembled into exosome membrane proteins-embedded nanoparticles(Exo-NPs).The Exo-NPs showed favorable targeting properties to their original cells.A photosensitizer,chlorin e6,was loaded into Exo-MBs to evaluate therapeutic efficacy as a drug *** higher therapeutic efficacy of photodynamic therapy was confirmed,followed by cancer immunotherapy from immunogenic cell *** have therefore developed a novel ultrasound image-guided drug delivery platform that overcomes the shortcomings of the conventional ultrasound contrast agent and is capable of simultaneous photodynamic therapy and cancer immunotherapy.

关键词： Exosomes Microbubbles Photodynamic therapy Ultrasound Sonoporation Cancer immunotherapy Drug delivery

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Development of Hair Follicle Dermal Papilla Spheroids Encapsulated in Alginate Hydrogel with Extracellular Matrix Protein

Development of Hair Follicle Dermal Papilla Spheroids Encaps...

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biomedical engineering International Conference (BMEiCON)

作者： Phasin Srinualchai Thanchanok Khorporn Patsawee Sriboonaied Peerapat Thongnuek Biomedical Engineering Program Faculty of Engineering Chulalongkorn University Bangkok Thailand Biomedical Materials and Devices for Revolutionary Integrative Systems Engineering (BMD-RISE) Research Unit Faculty of Engineering Biomedical Engineering Research Center Chulalongkorn University Bangkok Thailand

ISBN: (数字)9798331505431

ISBN: (纸本)9798331505448

Hair follicles (HF) are important anatomical structures that are responsible for maintenance of the hair cycle. However, hair disease can affect the hair follicle directly with the modern treatment still riddled with side effects due to lack of full understanding of hair nature. The study aimed to investigate the effect of alginate hydrogel with extracellular matrix (ECM) protein encapsulation on activity of dermal papilla (DP) spheroids. The DP cells were aggregated to mimic its native spherical structure and introduced into alginate solution mixed with ECM. The mixture was then crosslinked with calcium chloride to form hydrogel. The encapsulation elevated alkaline phosphatase (ALP) activity, which is a DP molecular marker. This work demonstrates that DP encapsulation in alginate with ECM can manipulate DP spheroid activity.

关键词： Encapsulation Proteins Protein engineering Three-dimensional displays Hydrogels Peptides Hafnium Hair follicle Maintenance Extracellular

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Characterization of Fluoride-added Hydroxyapatite Derived from Eggshells for Dental Application 15

Characterization of Fluoride-added Hydroxyapatite Derived fr...

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15th biomedical engineering International Conference, BMEiCON 2023

作者： Uthayaphamornwat, Vilasinee Khantachawana, Anak Kitiwan, Mettaya Srirussamee, Kasama Tunthawiroon, Phacharaphon School of Engineering Department of Biomedical Engineering Bangkok10520 Thailand Faculty of Engineering Department of Mechanical Engineering Bangkok10140 Thailand Biological Engineering Program Faculty of Engineering Bangkok10140 Thailand School of Science Department of Physics Bangkok10520 Thailand Devices and Systems for Energy and Environment Research Unit School of Science Bangkok10520 Thailand School of Engineering Department of Industrial Engineering Bangkok10520 Thailand

ISBN: (纸本)9798350345247

Hydroxyapatite (HA) is one of the potential biomaterials used for treating dental defects. It can be incorporated with fluoride to enhance its anti-caries properties, though other properties could be dependent on processing technique. Hence, this study aims to characterize the influence of sintering on the properties of fluoride-added HA derived from eggshells. FTIR and XRD techniques are used to characterize the chemical and crystal structures of the samples, whilst dissolution test is carried out to characterize material degradation in the acidic environment. The results show that sintering increased the crystallinity in both HA and fluoride-add HA (F-HA) samples, which corresponds with the enhanced stability during the dissolution test. Moreover, it is also found that the addition of fluoride could further stabilize the material structure, though the impurities found in all the samples still need to be minimized. These findings suggest that sintering and fluoride addition could potentially enhance anti-caries properties of eggshell-derived HA, which could be beneficial for dental application in future subject to further process optimization and analysis. © 2023 IEEE.

关键词： Hydroxyapatite

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Early Diagnosis of Osteoporosis: An Artificial Intelligence-Based Framework

Early Diagnosis of Osteoporosis: An Artificial Intelligence-...

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International Conference on Advances in biomedical engineering (ICABME)

作者： Amira J. Zaylaa Alaa Daher Mohammad Ayache Niveen Omeirat Razane Mahmoud Bader Abou Hawili Biomedical Engineering Laboratory Biomedical Engineering Program Electrical and Computer Engineering Faculty of Engineering Beirut Arab University Lebanon

Osteoporosis is a common disease characterized by low bone density and structural deterioration of bone tissue. For a successful course of treatment and fracture avoidance, early diagnosis of this disease is essential. The aim was to provide a novel method for osteoporosis prediction using Artificial Intelligence (AI)-based framework. The purpose was to predict the likelihood of osteoporosis based on the Bone Mineral Density (BMD), along with other characteristics such as age, weight, height, gender, and Body Mass Index (BMI) extracted from medical reports and images collected from a comprehensive medical center in Lebanon. Three machine-learning algorithms were implemented and tested, Logistic Regression (LR), Support Vector Machines (SVM), and Decision Trees (DT). Variety of quantitative statistical metrics were used to evaluate the performance of our framework, upon training and testing our algorithms. The metrics that were employed to evaluate our results included accuracy, precision, sensitivity, and F-score, in addition to the Receiver Operating Characteristic (ROC) Curve and the Area Under the Curve (AUC). Experimental Results demonstrated that both the SVM and LR algorithms achieved the highest accuracy of detection of osteoporosis as compared to existing algorithms applied in this field, with an accuracy of 89%. The sensitivity of diagnosis obtained was 98% by LR and 97% by SVM and surpassed the sensitivity obtained by DT. As such LR showed the best performance. The output of the algorithms could help medical doctors assess patients automatically. These findings demonstrated the potential of AI in osteoporosis prediction and thus prevention, highlighting the significance of early diagnosis. Thereby as a future prospect, choosing carefully the framework is crucial and additional algorithms have to be considered and tested.

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