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IEEE International Symposium on Biomedical Imaging

作者： Zhen Yuan Matthias C Schabel Anna L. David Victoria HJ Roberts Andrew Melbourne School of Biomedical Engineering and Image Sciences King's College London London UK Advanced Imaging Research Center Oregon Health & Science University Portland USA Utah Center for Advanced Imaging Research University of Utah Salt Lake City USA UCL EGA Institute for Women's Health University College London London UK Division of Reproductive & Developmental Sciences Oregon Health & Science University Portland USA

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

The placenta plays a crucial role in ensuring adequate oxygen delivery to the fetus. Despite being one of the most important organs in pregnancy, the placenta remains poorly understood. research into placental developmental structure and function has accelerated in recent years. The use of a preclinical pregnant nonhuman primate model allows researchers to quantify blood and oxygen transfer through the placenta and potentially improve our understanding of it. Furthermore, deploying Magnetic Resonance Imaging (MRI) to better understand the explicit function and mechanism of the placental vascular supply has become commonplace. Among these MRI techniques, T2, T2* and diffusivity are the most commonly deployed for accessing the pseudo-quantitative physical properties of the placenta. To enable better analysis of the placenta from MR images, and reduce the labour-intensive workload of manually delineating regions of interest, here we deployed a robust deep learning model trained on T2* MR images acquired from pregnant rhesus macaques, with the ground truth placenta segmentation drawn by our experts. After obtaining the trained model, we experimented with three segmentation fusion strategies aimed at merging the estimated segmentations from multi-echo times into one final outcome. For each fusion method, we conducted experiments to evaluate the effect of the automated segmentation on T2* estimation, including varying the echo time and the number of imaging slices. The best Dice score (averaging fusion method over 6 segmentations from different TE in one scan) reached 0.869. This work highlights the robustness of our trained segmentation model on nonhuman primate datasets and its potential for application in future preclinical studies. With appropriate fine-tuning, it could also be adapted for analysing human placental datasets.

关键词： Pregnancy Deep learning Image segmentation Translation Placenta Magnetic resonance imaging Pipelines Estimation Manuals Robustness

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Brain Causality Modeling Using Structure-Guided Spatiotemporal Diffusion Model for MCI Analysis 17th

Brain Causality Modeling Using Structure-Guided Spatiotempor...

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17th International Conference on Brain Informatics, BI 2024

作者： Zhu, Yanfei Wang, Jiangtao Cheng, Xuan Chen, Junyi Wei, Hui Lu, Libin Yang, Zhi Zuo, Qiankun School of Foreign Languages Sun Yat-sen University Guangzhou510275 China Hubei Key Laboratory of Digital Finance Innovation Hubei University of Economics Hubei Wuhan430205 China School of Information Engineering Hubei University of Economics Hubei Wuhan430205 China School of Mathematics and Computer Science Wuhan Polytechnic University Wuhan430023 China College of Electronics and Information Engineering Sichuan University Chengdu610065 China Hubei Internet Finance Information Engineering Technology Research Center Hubei University of Economics Hubei Wuhan430205 China

ISBN: (纸本)9789819632961

Early diagnosis of mild cognitive impairment (MCI) is crucial for the effective treatment and intervention of neurodegenerative diseases. Effective connectivity is one kind of brain network, which is helpful for analyzing the pathogenic mechanism of MCI. It is challenging to model causal relationships between brain regions from multimodal imaging data. This study proposes a new method for brain network causality modeling based on the structure-guided spatiotemporal diffusion model (SSDM), aiming to improve the accuracy of MCI diagnosis. By utilizing the advanced diffusion models, we introduced structural connectivity to guide the transformer-based network to learn topological and spatiotemporal features, which can better remove uncorrelated noise and improve effective connectivity estimation. The proposed model can not only generate temporal features of brain regions with individual differences but also construct discriminable effective connectivities. Experiments on the ADNI dataset demonstrate the effectiveness of our model, showing a certain improvement in diagnostic accuracy compared with competing methods. In addition, by analyzing the effective connectivities, our model predicts abnormal brain connections that are highly correlated with MCI. Overall, the framework proposed in this paper provides insights into the potential neurobiological mechanisms of MCI, which may promote early intervention strategies. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Neurodegenerative diseases

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Fundus Image Quality Assessment and Enhancement: a Systematic Review

arXiv

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arXiv 2025年

作者： Li, Heng Li, Haojin Ou, Mingyang Yu, Xiangyang Zhang, Xiaoqing Niu, Ke Fu, Huazhu Liu, Jiang Research Institute of Trustworthy Autonomous Systems SUSTech Shenzhen China Department of Computer Science and Engineering SUSTech Shenzhen China Center for High Performance Computing and Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Computer School Beijing Information Science and Technology University Beijing China Singapore

As an affordable and convenient eye scan, fundus photography holds the potential for preventing vision impairment, especially in resource-limited regions. However, fundus image degradation is common under intricate imaging environments, impacting following diagnosis and treatment. Consequently, image quality assessment (IQA) and enhancement (IQE) are essential for ensuring the clinical value and reliability of fundus images. While existing reviews offer some overview of this field, a comprehensive analysis of the interplay between IQA and IQE, along with their clinical deployment challenges, is lacking. This paper addresses this gap by providing a thorough review of fundus IQA and IQE algorithms, research advancements, and practical applications. We outline the fundamentals of the fundus photography imaging system and the associated interferences, and then systematically summarize the paradigms in fundus IQA and IQE. Furthermore, we discuss the practical challenges and solutions in deploying IQA and IQE, as well as offer insights into potential future research directions. Copyright © 2025, The Authors. All rights reserved.

关键词： Photography

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Enhanced Memory Performance in Ferroelectric NAND Applications: The Role of Tunnel Dielectric Position for Robust 10-Year Retention

Enhanced Memory Performance in Ferroelectric NAND Applicatio...

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2025 IEEE International Reliability Physics Symposium, IRPS 2025

作者： Venkatesan, Prasanna Padovani, Andrea Fernandes, Lance Ravikumar, Priyankka Park, Chinsung Tran, Huy Wang, Zekai Jayasankar, Hari Garlapati, Amrit Song, Taeyoung Chen, Hang Chern, Winston Wang, Zheng Kim, Kijoon Woog, Jongho Lim, Suhwan Kim, Kwangsoo Kim, Wanki Ha, Daewon Yu, Shimeng Dattal, Suman Larcher, Luca Thareja, Gaurav Khanl, Asif School of Electrical and Computer Engineering Georgia Institute of Technology GA United States University of Modena and Reggio Emilia Engineering Department 'Enzo Ferrari' Italy Institute of Electronics and Nanotechnology Georgia Institute of Technology GA United States Micron Technology United States Samsung Electronics Advanced Device Research Laboratory Semiconductor Research Center Korea Republic of School of Material Science and Engineering Georgia Institute of Technology GA United States Applied Materials United States

ISBN: (纸本)9798331504779

We report a comprehensive study on memory window (MW) enhancement and retention loss (RL) in ferroelectric (FE) field effect transistors for NAND applications with a dielectric layer inserted within the FE film (next to the gate GBL devices or in the middle of the FE layer TDL devices). Using a temperature-dependent modeling framework, we show that MW and RL properties are controlled respectively by carriers trapping into defects at the dielectric-FE interface and by its fragile balance with FE depolarization. While MW enhancement is achieved whenever the inserted dielectric layer is present, a robust retention is obtained only in TDL FEFETs, thanks to a stabilization of the trapped charge preventing FE depolarization. Simulation results clearly demonstrate that the fragile balance between above phenomena is ultimately controlled by the position of the dielectric layer, which determines i) the field redistribution within the stack, ii) the magnitude of charge de-trapping, and iii) the magnitude of the depolarization field. Our results provide critical guidelines for the improvement of FE 3D-NAND reliability. © 2025 IEEE.

关键词： Ferroelectric films

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Detection of Bleeding Events In EHR Notes Using A Graph Dynamic Autoencoder Based Riemannian Residual Neural Network

Detection of Bleeding Events In EHR Notes Using A Graph Dyna...

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International Conference on ICT in Business Industry & Government (ICTBIG)

作者： V. R. Niveditha H. Mohammed Ali S. Radha Rammohan Rajababu D R Maranan S. Kaliappan Department of Computer Science and Engineering Sathyabama Institute of Science and Technology Chennai Department of Mechanical Engineering SRM Institute of Science and Technology Chennai Center for Open and Digital Education Hindustan University Chennai Department of Electrical and Electronics Engineering SR University Warangal Telangana Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai Tamil Nadu India Division of Research and Development Lovely Professional University Phagwara Punjab India

ISBN: (数字)9798331518981

ISBN: (纸本)9798331518998

Identifying occurrences of abnormal bleeding based on unstructured and structured medical data, such as patient notes, vitals, and laboratory findings, is the problem of recognising bleeding events in Electronic Health Records (EHR). The problem is in accurately recognising these occurrences by analysing temporal patterns, extracting significant information, and distinguishing catastrophic bleeding occasions from typical medical fluctuations given the complexity of EHR data, which is frequently longitudinal, heterogeneous, and packed with noise. The goal is to create a Graph Dynamic Autoencoder combined with a Riemannian Residual Neural Network (GDA-RRNN) with Elk Herd optimizer (EHO) model that can identify and display bleeding incidents in electronic medical data. The EHO optimizes the hyperparameters GDA-RRNN to improve the performance of the suggested method. We extracted 300 electronic health records that contained leukaemia or bleeding diagnostic codes from the International categorization of Diseases, Tenth Revision. The electronic health record has annotations indicating whether a sentence was positive or negative for bleeding. A proposed model that can identify bleeding at the sentence and note levels was created using the annotated texts. The best-performing suggested approach achieved a sensitivity of 0.99, specificity of 0.99, and a negative prediction value of 0.99 on an equal test set of 1178 phrases.

关键词： Sensitivity Codes Annotations Autoencoders Data models Hemorrhaging Electronic medical records Medical diagnostic imaging Residual neural networks Diseases

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Synergistic Effects of Bimetallic Pd-Au(Alloy)/Sno2 Nanocomposites for Low Temperature and Selective Hydrogen Gas Sensors

SSRN

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SSRN 2023年

作者： Kim, Dong-Seog Ahemad, Mohammad Jamir Le, Thanh Duc Lee, Hu-Jun Yu, Yeon-Tae Division of Advanced Materials Engineering Research Center for Advanced Materials Development Jeonbuk National University Jeonju54896 Korea Republic of Department of Materials Science and Engineering Kyushu University 744 Motooka Nishi-ku Fukuoka819-0395 Japan

In view of the explosive nature of hydrogen gas, the demand for detection is increasing. Although Pd-based chemiresistive sensors are gaining much attention in hydrogen detection, it is easily oxidized at high temperatures, leading to the deterioration of sensing performance. To address this issue, we synthesized bimetallic Pd-Au alloy nanoparticles (NPs) and mixed them with SnO2 powder for improving the hydrogen sensing performance. The response of the bimetallic Pd-Au(alloy)/SnO2 nanocomposites (NCs) sensor toward 100 ppm hydrogen was 72.78 which is 7 times higher than that of the pure SnO2 sensor at a relatively lower working temperature of 150°C. Furthermore, when compared to other interfering gases, the sensor revealed high selectivity for hydrogen gas. The enhanced hydrogen sensing performance was attributed to the synergistic effect arising from the formation of a heterojunction interface between Pd-Au alloy and SnO2 NPs and the decomposition and absorption of hydrogen molecules by Pd-Au alloy NPs. © 2023, The Authors. All rights reserved.

关键词： Binary alloys

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Observation of Photonic Chiral Flatbands

引用

Physical Review Letters 2025年第10期134卷 103801-103801页

作者： Minho Choi Andrea Alù Arka Majumdar Department of Electrical and Computer Engineering University of Washington Seattle Washington 98195 USA Photonics Initiative Advanced Science Research Center City University of New York New York New York 10031 USA and Physics Program Graduate Center City University of New York New York New York 10031 USA Department of Electrical and Computer Engineering University of Washington Seattle Washington 98195 USA and Department of Physics University of Washington Seattle Washington 98195 USA

Distinct selectivity to the spin angular momenta of photons has garnered significant attention in recent years, for its relevance in basic science and for imaging and sensing applications. While nonlocal metasurfaces with strong chiral responses to the incident light have been reported, these responses are typically limited to a narrow range of incident angles. In this study, we demonstrate a nonlocal metasurface that showcases strong chirality, characterized by circular dichroism (∼0.6), over a wide range of incident angles ±5°. Its quality factor, circular dichroism and resonant frequency can be optimized by design. These findings pave the way to further advance the development of valley-selective optical cavities and augmented reality applications.

关键词： Natural frequencies

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Robust globally divergence-free HDG finite element method for steady thermally coupled incompressible MHD flow

arXiv

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arXiv 2024年

作者： Zhang, Min Zhu, Zimo Zhai, Qijia Xie, Xiaoping Institute of Mathematics Henan Academy of Sciences Zhengzhou450046 China College of Mathematies and Information Science Henan Normal University Xinxiang453007 China Chengdu aircraft design and Research Institute Chengdu610041 China School of Mathematics Sichuan University Chengdu610064 China Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal23955 Saudi Arabia

This paper develops an hybridizable discontinuous Galerkin (HDG) finite element method of arbitrary order for the steady thermally coupled incompressible Magnetohydrodynamics (MHD) flow. The HDG scheme uses piecewise polynomials of degrees k(k ≥ 1), k, k − 1, k − 1 and k respectively for the approximations of the velocity, the magnetic field, the pressure, the magnetic pseudo-pressure, and the temperature in the interior of elements, and uses piecewise polynomials of degree k for their numerical traces on the interfaces of elements. The method is shown to yield globally divergence-free approximations of the velocity and magnetic fields. Existence and uniqueness results for the discrete scheme are given and optimal a priori error estimates are derived. Numerical experiments are provided to verify the obtained theoretical results. © 2024, CC BY.

关键词： Galerkin methods

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Feature Selection for Detecting ICMPv6-Based DDoS Attacks Using Binary Flower Pollination Algorithm

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computer Systems science & engineering 2023年第10期47卷 553-574页

作者： Adnan Hasan Bdair Aighuraibawi Selvakumar Manickam Rosni Abdullah Zaid Abdi Alkareem Alyasseri Ayman Khallel Dilovan Asaad Zebari Hussam Mohammed Jasim Mazin Mohammed Abed Zainb Hussein Arif National Advanced IPv6 Centre(NAv6) Universiti Sains MalaysiaPenang11800Malaysia Baghdad College of Economic Sciences University BaghdadIraq School of Computer Sciences Universiti Sains MalaysPenang11800Malaysia Information Technology Research and Development Center University of KufaNajafIraq College of Engineering University of Warith Al-AnbiyaaKarbalaIraq Faculty of Computing and Informatics Universiti Malaysia SabahSabahMalaysia Business Administration College of Administration and Financial SciencesImam Ja’afar Al-Sadiq UniversityBaghdad10001Iraq College of Computer Science and Information Technology University of AnbarRamadi AnbarIraq Department of Computer Science College of ScienceNawroz UniversityDuhok42001Kurdistan RegionIraq

Internet Protocol version 6(IPv6)is the latest version of IP that goal to host 3.4×10^(38)unique IP addresses of devices in the ***6 has introduced new features like Neighbour Discovery Protocol(NDP)and Address Auto-configuration ***6 needed several protocols like the Address Auto-configuration Scheme and Internet Control Message Protocol(ICMPv6).IPv6 is vulnerable to numerous attacks like Denial of Service(DoS)and Distributed Denial of Service(DDoS)which is one of the most dangerous attacks executed through ICMPv6 messages that impose security and financial ***,an Intrusion Detection System(IDS)is a monitoring system of the security of a network that detects suspicious activities and deals with amassive amount of data comprised of repetitive and inappropriate features which affect the detection rate.A feature selection(FS)technique helps to reduce the computation time and complexity by selecting the optimum subset of *** paper proposes a method for detecting DDoS flooding attacks(FA)based on ICMPv6 messages using a Binary Flower PollinationAlgorithm(BFPA-FA).The proposed method(BFPA-FA)employs FS technology with a support vector machine(SVM)to identify the most relevant,influential ***,The ICMPv6-DDoS dataset was used to demonstrate the effectiveness of the proposed method through different attack *** results show that the proposed method BFPAFA achieved the best accuracy rate(97.96%)for the ICMPv6 DDoS detection with a reduced number of features(9)to half the total(19)*** proven proposed method BFPA-FAis effective in the ICMPv6 DDoS attacks via IDS.

关键词： IPv6 ICMPv6 DDoS feature selection flower pollination algorithm anomaly detection

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Controllable multi-level switching of optical phase change materials via microheater temperature profile engineering

Controllable multi-level switching of optical phase change m...

引用

2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Sun, Hongyi Lian, Chuanyu Vásquez-Aza, Francis Huang, Yi-Siou Vitale, Steven A. Takeuchi, Ichiro Hu, Juejun Youngblood, Nathan Pavlidis, Georges Ríos Ocampo, Carlos A. Department of Materials Science & Engineering University of Maryland College ParkMD20742 United States Institute for Research in Electronics and Applied Physics University of Maryland College ParkMD20742 United States Department of Mechanical Engineering University of Connecticut StorrsCT06269 United States Advanced Materials and Microsystems Group MIT Lincoln Laboratory LexingtonMA02139 United States Quantum Materials Center Department of Physics University of Maryland College ParkMD20742 United States Department of Materials Science & Engineering MIT CambridgeMA02139 United States Electrical & Computer Engineering Department The University of Pittsburgh PittsburghPA15213 United States

ISBN: (纸本)9781957171395

We demonstrate doped-silicon-on-insulator microheaters with triangle-like temperature profiles. Such devices control the hotspot size and temperature and, thus, the area that undergoes amorphization or crystallization in optical phase-change materials, leading to controllable multilevel, nonvolatile response. © Optica Publishing Group 2024 © 2024 The Author(s)

关键词： Optical materials

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