检索结果-内蒙古大学图书馆

Assessing Trustworthy AI in Times of COVID-19: Deep Learning for Predicting a Multiregional Score Conveying the Degree of Lung Compromise in COVID-19 Patients

IEEE Transactions on Technology and Society

引用

IEEE Transactions on Technology and Society 2022年第4期3卷 272-289页

作者： Allahabadi, Himanshi Amann, Julia Balot, Isabelle Beretta, Andrea Binkley, Charles Bozenhard, Jonas Bruneault, Frederick Brusseau, James Candemir, Sema Cappellini, Luca Alessandro Chakraborty, Subrata Cherciu, Nicoleta Cociancig, Christina Coffee, Megan Ek, Irene Espinosa-Leal, Leonardo Farina, Davide Fieux-Castagnet, Genevieve Frauenfelder, Thomas Gallucci, Alessio Giuliani, Guya Golda, Adam Van Halem, Irmhild Hildt, Elisabeth Holm, Sune Kararigas, Georgios Krier, Sebastien A. Kuhne, Ulrich Lizzi, Francesca Madai, Vince I. Markus, Aniek F. Masis, Serg Mathez, Emilie Wiinblad Mureddu, Francesco Neri, Emanuele Osika, Walter Ozols, Matiss Panigutti, Cecilia Parent, Brendan Pratesi, Francesca Moreno-Sanchez, Pedro A. Sartor, Giovanni Savardi, Mattia Signoroni, Alberto Sormunen, Hanna-Maria Spezzatti, Andy Srivastava, Adarsh Stephansen, Annette F. Theng, Lau Bee Tithi, Jesmin Jahan Tuominen, Jarno Umbrello, Steven Vaccher, Filippo Vetter, Dennis Westerlund, Magnus Wurth, Renee Zicari, Roberto V. Ey Netherlands Enterprise Intelligence Department Amsterdam1083 HP Netherlands Eth Zurich Health Ethics and Policy Lab Department of Health Sciences and Technology Zürich8092 Switzerland Center for Diplomatic and Strategic Studies Postgraduate Studies in Diplomacy and International Relations Paris75015 France Pisa56124 Italy Hackensack Meridian Health Bioethics Center EdisonNJ08820 United States University of Oxford Faculty of Philosophy OxfordOX2 6GG United Kingdom Collège André- Laurendeau Philosophie Department MontrealQCH8N 2J4 Canada Université du Québec À Montréal École des Médias MontrealQCH2L 2C4 Canada Pace University Philosophy Department New YorkNY10038 United States The Ohio State University Wexner Medical Center Department of Radiology ColumbusOH43210 United States Humanitas Research Hospital Department of Radiology Milan20089 Italy Humanitas University Department of Biomedical Sciences Milan20089 Italy University of New England Faculty of Science Agriculture Business and Law ArmidaleNSW2351 Australia University of Technology Sydney Faculty of Engineering and Information Technology SydneyNSW2007 Australia Scuola Superiore Sant'Anna European Centre of Excellence on the Regulation of Robotics and Ai Pisa56127 Italy University of Bremen Group of Computer Architecture Bremen28359 Germany New York University Grossman School of Medicine Division of Infectious Diseases and Immunology Department of Medicine New YorkNY10016 United States Digital Institute Ai Research Section Stockholm16731 Sweden Arcada University of Applied Sciences Department of Business Management and Analytics Helsinki00550 Finland University of Brescia Radiological Sciences and Public Health Department of Medical and Surgical Specialties Brescia25121 Italy Sncf Reseau Sa Ethique Groupe La Plaine93418 France Institute of Diagnostic and Interventional Radiology University Hospital Zurich Zürich8091 Switzerland Eindhoven University of Tech

This article's main contributions are twofold: 1) to demonstrate how to apply the general European Union's High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare and 2) to investigate the research question of what does 'trustworthy AI' mean at the time of the COVID-19 pandemic. To this end, we present the results of a post-hoc self-assessment to evaluate the trustworthiness of an AI system for predicting a multiregional score conveying the degree of lung compromise in COVID-19 patients, developed and verified by an interdisciplinary team with members from academia, public hospitals, and industry in time of pandemic. The AI system aims to help radiologists to estimate and communicate the severity of damage in a patient's lung from Chest X-rays. It has been experimentally deployed in the radiology department of the ASST Spedali Civili clinic in Brescia, Italy, since December 2020 during pandemic time. The methodology we have applied for our post-hoc assessment, called Z-Inspection®, uses sociotechnical scenarios to identify ethical, technical, and domain-specific issues in the use of the AI system in the context of the pandemic. © 2020 IEEE.

关键词： COVID-19

来源：评论

学校读者我要写书评

暂无评论

Multilevel and multifidelity uncertainty quantification for cardiovascular hemodynamics

arXiv

引用

arXiv 2019年

作者： Fleeter, Casey M. Geraci, Gianluca Schiavazzi, Daniele E. Kahn, Andrew M. Marsden, Alison L. Institute for Computational and Mathematical Engineering Stanford University StanfordCA United States Center for Computing Research Sandia National Laboratories AlbuquerqueNM United States Department of Applied and Computational Mathematics and Statistics University of Notre Dame Notre DameIN United States Department of Medicine University of California San Diego San diegoCA United States Departments of Pediatrics and Bioengineering Stanford University StanfordCA United States

Standard approaches for uncertainty quantification in cardiovascular modeling pose challenges due to the large number of uncertain inputs and the significant computational cost of realistic three-dimensional simulations. We propose an efficient uncertainty quantification framework utilizing a multilevel multifidelity Monte Carlo (MLMF) estimator to improve the accuracy of hemodynamic quantities of interest while maintaining reasonable computational cost. This is achieved by leveraging three cardiovascular model fidelities, each with varying spatial resolution to rigorously quantify the variability in hemodynamic outputs. We employ two low-fidelity models (zero- and one-dimensional) to construct several different estimators. Our goal is to investigate and compare the efficiency of estimators built from combinations of these two low-fidelity model alternatives and our high-fidelity three-dimensional models. We demonstrate this framework on healthy and diseased models of aortic and coronary anatomy, including uncertainties in material property and boundary condition parameters. Our goal is to demonstrate that for this application it is possible to accelerate the convergence of the estimators by utilizing a MLMF paradigm. Therefore, we compare our approach to single fidelity Monte Carlo estimators and to a multilevel Monte Carlo approach based only on three-dimensional simulations, but leveraging multiple spatial resolutions. We demonstrate significant, on the order of 10 to 100 times, reduction in total computational cost with the MLMF estimators. We also examine the differing properties of the MLMF estimators in healthy versus diseased models, as well as global versus local quantities of interest. As expected, global quantities such as outlet pressure and flow show larger reductions than local quantities, such as those relating to wall shear stress, as the latter rely more heavily on the highest fidelity model evaluations. Similarly, healthy models show larger reducti

关键词： Monte Carlo methods

来源：评论

学校读者我要写书评

暂无评论

Activating Bip-orbitals in Dispersed Clusters of Amorphous BiOxfor Electrocatalytic Nitrogen Reduction

引用

Angewandte Chemie 2023年第15期135卷

作者： Dr. Jianxin Kang Xiangyu Chen Rutong Si Prof. Xiang Gao Prof. Shuo Zhang Prof. Gilberto Teobaldi Prof. Annabella Selloni Li-Min Liu Prof. Lin Guo School of Chemistry Beijing Advanced Innovation Center for Biomedical Engineering Key Laboratory of Bio-Inspired Smart Interfacial Science and Technology Beihang University Beijing 100191 China Beijing Computational Science Research Center Beijing 100193 China School of Physics Beihang University Beijing 100191 China Center for High Pressure Science and Technology Advanced Research Beijing 100190 China Shanghai Synchrotron Radiation Facility Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai 201204 China Scientific Computing Department STFC UKRI Rutherford Appleton Laboratory Didcot OX11 0QX UK School of Chemistry University of Southampton Highfield Southampton SO17 1BJ UK Department of Chemistry Princeton University Princeton NJ 08544 USA

Catalytic strategies based on main group metals are significantly less advanced than those of transition metal catalysis, leaving untapped areas of potentially fruitful research. We here demonstrate an effective approach for the modulation of Bi 6p energy levels during the construction of atomically dispersed clusters of amorphous BiO x . Bi oxidation state is proposed to strongly affects the nitrogen fixation activity, with the half-occupied p z orbitals of the Bi 2+ ions being highly efficient toward electron injection into the inert N 2 molecule. With sufficient catalytic sites to adsorb and activate N 2 , the bonding between N 2 and catalyst is able to be in situ identified. The catalyst shows an outstanding Faraday efficiency (≈30 %) and high yield (≈113 μg h −1 mg −1 cat ) in NH 3 production, outperforming most of the existing catalysts in aqueous solution. These results lay the basis for developing the potential of p- block elements for catalysis of multi-electron reactions.

关键词： Amorphous Nanomaterial Electrocatalysis In Situ Identification Nitrogen Fixation p-Orbitals

来源：评论

学校读者我要写书评

暂无评论

Supervised learning for quantum maximum entropy estimation

arXiv

引用

arXiv 2020年

作者： Cao, Ningping Xie, Jie Zhang, Aonan Hou, Shi-Yao Zhang, Lijian Zeng, Bei Department of Mathematics & Statistics University of Guelph GuelphONN1G 2W1 Canada Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada National Laboratory of Solid State Microstructures College of Engineering and Applied Sciences School of Physics Nanjing University Nanjing210093 China Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing210093 China College of Physics and Electronic Engineering Center for Computational Sciences Sichuan Normal University Chengdu610068 China Department of Physics Hong Kong University of Science and Technology Clear Water Bay Kowloon Hong Kong

For an unknown quantum state ρ, a set of measurement outcomes provides partial information. The principe of maximum entropy states that the density matrix which best represents the current knowlege is the one with the maximum entropy. However, the maximum entropy estimation (MEE) is hard to calculate in general. In this work, we develop a method that outputs an approximation to the MEE from limited measurement results by using supervised learning techniques. The method estimates the MEE of theoretical data of several different quantum systems with high fidelities. We also test our method experimentally with a photonic set-up, which exhibits high fidelities (all greater than 99.7%) and robustness against experimental errors. In comparison with previous known optimization algorithms for MEE, our method provides adequate fidelities with high efficiency. Copyright © 2020, The Authors. All rights reserved.

关键词： Quantum optics

来源：评论

学校读者我要写书评

暂无评论

On energy dissipation theory and numerical stability for time-fractional phase field equations

arXiv

引用

arXiv 2018年

作者： Tang, Tao Yu, Haijun Zhou, Tao Department of Mathematics Southern University of Science and Technology Shenzhen China NCMIS LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing China

For the time-fractional phase field models, the corresponding energy dissipation law has not been settled on both the continuous level and the discrete level. In this work, we shall address this open issue. More precisely, we prove for the first time that the time-fractional phase field models indeed admit an energy dissipation law of an integral type. In the discrete level, we propose a class of finite difference schemes that can inherit the theoretical energy stability. Our discussion covers the time-fractional gradient systems, including the time-fractional Allen-Cahn equation, the time-fractional Cahn-Hilliard equation, and the time-fractional molecular beam epitaxy models. Numerical examples are presented to confirm the theoretical results. Moreover, a numerical study of the coarsening rate of random initial states depending on the fractional parameter α reveals that there are several coarsening stages for both time-fractional Cahn-Hilliard equation and timefractional molecular beam epitaxy model, while there exists a -α/3 power law coarsening *** Codes 65M12, 65M06, 35Q99, 74A50 Copyright © 2018, The Authors. All rights reserved.

关键词： Energy dissipation

来源：评论

学校读者我要写书评

暂无评论

NMRCloudQ： a quantum cloud experience on a nuclear magnetic resonance quantum computer

引用

Science Bulletin 2018年第1期63卷 17-23页

作者： Tao Xin Shilin Huang Sirui Lu Keren Li Zhihuang Luo Zhangqi Yin Jun Li Dawei Lu Guilu Long Bei Zeng Department of Physics Tsinghua University Beijing 100084 China Center for Quantum Information Institute for Interdiscriplinary Information Sciences Tsinghua University Belting 100084 China Beijing Computational Science Research Center Beijing 100193 China Institute for Quantum Computing University of Waterloo waterloo N2L 3C1 Ontario Canada Department of Physics and Institute for Quantum Science and Engineering Southern University of Science and Technology Shenzhen 518055 China The Innovative Center of Quantum Matter Beijing 100084 China Department of Mathematics and Statistics University of Guelph Guelph N1C 2W1 Ontario Canada

Cloud-based quantum computing is anticipated to be the most useful and reachable form for public users to experience with the power of quantum. As initial attempts, IBM Q has launched influential cloud services on a superconducting quantum processor in 2016, but no other platforms has followed up yet. Here,we report our new cloud quantum computing service – NMRCloud Q(http://***/zh-hans/),where nuclear magnetic resonance, one of the pioneer platforms with mature techniques in experimental quantum computing, plays as the role of implementing computing tasks. Our service provides a comprehensive software environment preconfigured with a list of quantum information processing packages,and aims to be freely accessible to either amateurs that look forward to keeping pace with this quantum era or professionals that are interested in carrying out real quantum computing experiments in person. In our current version, four qubits are already usable with in average 99.10% single-qubit gate fidelity and 97.15% two-qubit fidelity via randomized benchmaking tests. Improved control precisions as well as a new seven-qubit processor are also in preparation and will be available later.

关键词： Quantum cloud Nuclear magnetic resonance Gradient ascent pulse engineering Randomized benchmarking

来源：评论

学校读者我要写书评

暂无评论

Waveform Modelling for the Laser Interferometer Space Antenna

arXiv

引用

arXiv 2023年

作者： Afshordi, Niayesh Akçay, Sarp Seoane, Pau Amaro Antonelli, Andrea Aurrekoetxea, Josu C. Barack, Leor Barausse, Enrico Benkel, Robert Bernard, Laura Bernuzzi, Sebastiano Berti, Emanuele Bonetti, Matteo Bonga, Béatrice Bozzola, Gabriele Brito, Richard Buonanno, Alessandra Cárdenas-Avendaño, Alejandro Casals, Marc Chernoff, David F. Chua, Alvin J.K. Clough, Katy Colleoni, Marta Compère, Geoffrey Dhesi, Mekhi Druart, Adrien Durkan, Leanne Faye, Guillaume Ferguson, Deborah Field, Scott E. Gabella, William E. García-Bellido, Juan Gracia-Linares, Miguel Gerosa, Davide Green, Stephen R. Haney, Maria Hannam, Mark Heffernan, Anna Hinderer, Tanja Helfer, Thomas Hughes, Scott A. Husa, Sascha Isoyama, Soichiro Katz, Michael L. Kavanagh, Chris Khanna, Gaurav Kidder, Larry E. Korol, Valeriya Küchler, Lorenzo Laguna, Pablo Larrouturou, François Le Tiec, Alexandre Leather, Benjamin Lim, Eugene A. Lim, Hyun Littenberg, Tyson B. Long, Oliver Lousto, Carlos O. Lovelace, Geoffrey Lukes-Gerakopoulos, Georgios Lynch, Philip Macedo, Rodrigo P. Markakis, Charalampos Maggio, Elisa Mandel, Ilya Maselli, Andrea Mathews, Josh Mourier, Pierre Neilsen, David Nagar, Alessandro Nichols, David A. Novák, Jan Okounkova, Maria O’Shaughnessy, Richard Oshita, Naritaka O’Toole, Conor Pan, Zhen Pani, Paolo Pappas, George Paschalidis, Vasileios Pfeiffer, Harald P. Pompili, Lorenzo Pound, Adam Pratten, Geraint Rüter, Hannes R. Ruiz, Milton Sam, Zeyd Sberna, Laura Shapiro, Stuart L. Shoemaker, Deirdre M. Sopuerta, Carlos F. Spiers, Andrew Sundar, Hari Tamanini, Nicola Thompson, Jonathan E. Toubiana, Alexandre Tsokaros, Antonios Upton, Samuel D. van de Meent, Maarten Vernieri, Daniele Wachter, Jeremy M. Warburton, Niels Wardell, Barry Witek, Helvi Witzany, Vojtěch Yang, Huan Zilhão, Miguel Albertini, Angelica Arun, K.G. Bezares, Miguel Bonilla, Alexander Chapman-Bird, Christian Cownden, Bradley Cunningham, Kevin Devitt, Chris Dolan, Sam Duque, Francisco Dyson, Conor Fryer, Chris L. Gair, Jonathan R. Giacomazzo, Bruno Gupta, Priti Han, Wen-Biao Haas, Roland Perimeter Institute for Theoretical Physics WaterlooONN2L 2Y5 Canada School of Mathematics and Statistics University College Dublin Belfield Dublin 4 Ireland Universitat Politècnica de València València Spain Max Planck Institute for Extraterrestrial Physics Garching Germany Higgs Centre for Theoretical Physics Edinburgh United Kingdom Kavli Institute for Astronomy and Astrophysics Beijing100871 China William H. Miller III Department of Physics and Astronomy Johns Hopkins University BaltimoreMD21218 United States Astrophysics University of Oxford Denys Wilkinson Building Keble Road OxfordOX1 3RH United Kingdom School of Mathematical Sciences and STAG Research Centre University of Southampton SouthamptonSO17 1BJ United Kingdom SISSA Via Bonomea 265 Trieste34136 Italy INFN Sezione di Trieste IFPU Institute for Fundamental Physics of the Universe Via Beirut 2 Trieste34014 Italy Max Planck Institute for Gravitational Physics Albert Einstein Institute PotsdamD-14476 Germany Laboratoire Univers et Théories CNRS Observatoire de Paris Université PSL Université Paris Cité Meudon92190 France Theoretisch-Physikalisches Institut Friedrich-Schiller-Universität Jena Jena07743 Germany Dipartimento di Fisica "G. Occhialini" Universitá degli Studi di Milano-Bicocca Piazza della Scienza 3 Milano20126 Italy INFN Sezione di Milano-Bicocca Piazza della Scienza 3 Milano20126 Italy Institute for Mathematics Astrophysics and Particle Physics Radboud University Nijmegen6525 AJ Netherlands The University of Arizona Department of Astronomy TucsonAZ85721 United States CENTRA Departamento de Física Instituto Superior Técnico – IST Universidade de Lisboa – UL Avenida Rovisco Pais 1 Lisboa1049-001 Portugal Princeton Gravity Initiative Princeton University PrincetonNJ08544 United States Institut für Theoretische Physik Universität Leipzig Brüderstraße 16 Leipzig04103 Germany Rio de JaneiroCEP 22290-180 Brazil Department of Astronomy Cornell Univers

LISA, the Laser Interferometer Space Antenna, will usher in a new era in gravitational-wave astronomy. As the first anticipated space-based gravitational-wave detector, it will expand our view to the millihertz gravitational-wave sky, where a spectacular variety of interesting new sources abound: from millions of ultra-compact binaries in our Galaxy, to mergers of massive black holes at cosmological distances;from the beginnings of inspirals that will venture into the ground-based detectors’ view to the death spiral of compact objects into massive black holes, and many sources in between. Central to realising LISA’s discovery potential are waveform models, the theoretical and phenomenological predictions of the pattern of gravitational waves that these sources emit. This white paper is presented on behalf of the Waveform Working Group for the LISA Consortium. It provides a review of the current state of waveform models for LISA sources, and describes the significant challenges that must yet be overcome. © 2023, CC BY.

关键词： Gravity waves

来源：评论

学校读者我要写书评

暂无评论

XACC: A System-Level Software Infrastructure for Heterogeneous Quantum-Classical computing∗

arXiv

引用

arXiv 2019年

作者： McCaskey, Alexander J. Lyakh, Dmitry I. Dumitrescu, Eugene F. Powers, Sarah S. Humble, Travis S. Quantum Computing Institute Oak Ridge National Laboratory Oak RidgeTN37831 United States Computer Science and Mathematics Division Oak Ridge National Laboratory Oak RidgeTN37831 United States National Center for Computational Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States

Quantum programming techniques and software have advanced significantly over the past five years, with a majority focusing on high-level language frameworks targeting remote REST library APIs. As quantum computing architectures advance and become more widely available, lower-level, system software infrastructures will be needed to enable tighter, co-processor programming and access models. Here we present XACC, a system-level software infrastructure for quantum-classical computing that promotes a service-oriented architecture to expose interfaces for core quantum programming, compilation, and execution tasks. We detail XACC’s interfaces, their interactions, and its implementation as a hardware-agnostic framework for both near-term and future quantum-classical architectures. We provide concrete examples demonstrating the utility of this framework with paradigmatic tasks. Our approach lays the foundation for the development of compilers, associated runtimes, and low-level system tools tightly integrating quantum and classical workflows. Copyright © 2019, The Authors. All rights reserved.

关键词： Computer architecture

来源：评论

学校读者我要写书评

暂无评论

Benchmarking the CoW with the TopCoW Challenge: Topology-Aware Anatomical Segmentation of the Circle of Willis for CTA and MRA

arXiv

引用

arXiv 2023年

作者： Yang, Kaiyuan Musio, Fabio Ma, Yihui Juchler, Norman Paetzold, Johannes C. Al-Maskari, Rami Höher, Luciano Li, Hongwei Bran Hamamci, Ibrahim Ethem Sekuboyina, Anjany Shit, Suprosanna Huang, Houjing Prabhakar, Chinmay de la Rosa, Ezequiel Waldmannstetter, Diana Kofler, Florian Navarro, Fernando Menten, Martin Ezhov, Ivan Rueckert, Daniel Vos, Iris Ruigrok, Ynte Velthuis, Birgitta Kuijf, Hugo Hämmerli, Julien Wurster, Catherine Bijlenga, Philippe Westphal, Laura Bisschop, Jeroen Colombo, Elisa Baazaoui, Hakim Makmur, Andrew Hallinan, James Wiestler, Bene Kirschke, Jan S. Wiest, Roland Montagnon, Emmanuel Letourneau-Guillon, Laurent Galdran, Adrian Galati, Francesco Falcetta, Daniele Zuluaga, Maria A. Lin, Chaolong Zhao, Haoran Zhang, Zehan Ra, Sinyoung Hwang, Jongyun Park, Hyunjin Chen, Junqiang Wodzinski, Marek Müller, Henning Shi, Pengcheng Liu, Wei Ma, Ting Yalçin, Cansu Hamadache, Rachika E. Salvi, Joaquim Llado, Xavier Estrada, Uma Maria Lal-Trehan Abramova, Valeriia Giancardo, Luca Oliver, Arnau Liu, Jialu Huang, Haibin Cui, Yue Lin, Zehang Liu, Yusheng Zhu, Shunzhi Patel, Tatsat R. Tutino, Vincent M. Orouskhani, Maysam Wang, Huayu Mossa-Basha, Mahmud Zhu, Chengcheng Rokuss, Maximilian R. Kirchhoff, Yannick Disch, Nico Holzschuh, Julius Isensee, Fabian Maier-Hein, Klaus Sato, Yuki Hirsch, Sven Wegener, Susanne Menze, Bjoern Department of Quantitative Biomedicine University of Zurich Zurich Switzerland Center for Computational Health Zurich University of Applied Sciences Zurich Switzerland Department of Neuroradiology University Hospital of Zurich Zurich Switzerland Department of Neurosurgery Zhongnan Hospital of Wuhan University Wuhan China Department of Computing Imperial College London London United Kingdom Helmholtz Center Munich Germany Athinoula A. Martinos Center for Biomedical Imaging Harvard Medical School Boston United States School of Medicine Technical University of Munich Munich Germany Department of Informatics Technical University of Munich Munich Germany Helmholtz AI Helmholtz Munich Munich Germany Image Sciences Institute UMC Utrecht Utrecht Netherlands Department of Neurology UMC Utrecht Utrecht Netherlands Department of Radiology UMC Utrecht Utrecht Netherlands Department of Clinical Neurosciences Division of Neurosurgery Geneva University Hospitals Geneva Switzerland Department of Neurology University Hospital of Zurich Zurich Switzerland Department of Physiology University of Toronto Toronto Canada Department of Neurosurgery University Hospital of Zurich Zurich Switzerland Department of Diagnostic Imaging National University Hospital Singapore Department of Diagnostic and Interventional Neuroradiology University Hospital Berne University of Berne Berne Switzerland Montreal Canada Universitat Pompeu Fabra Barcelona Spain EURECOM Biot France Institute of Medical Technology Peking University Health Science Center Beijing China Hangzhou Genlight Medtech Co. Ltd. Hangzhou China Department of Artificial Intelligence Sungkyunkwan University Seoul Korea Republic of Department of Electrical and Computer Engineering Sungkyunkwan University Seoul Korea Republic of Shanghai MediWorks Precision Instruments Co. Ltd. Shanghai China Institute of Informatics HES-SO Valais-Wallis Switzerland Department of Measurement and Electronics AGH University

The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to affect the risk, severity, and clinical outcome of serious neuro-vascular diseases. However, characterizing the highly variable CoW anatomy is still a manual and time-consuming expert task. The CoW is usually imaged by two angiographic imaging modalities, magnetic resonance angiography (MRA) and computed tomography angiography (CTA), but there exist limited public datasets with annotations on CoW anatomy, especially for CTA. Therefore we organized the TopCoW Challenge in 2023 with the release of an annotated CoW dataset. The TopCoW dataset was the first public dataset with voxel-level annotations for thirteen possible CoW vessel components, enabled by virtual-reality (VR) technology. It was also the first large dataset with paired MRA and CTA from the same patients. TopCoW challenge formalized the CoW characterization problem as a multiclass anatomical segmentation task with an emphasis on topological metrics. We invited submissions worldwide for the CoW segmentation task, which attracted over 140 registered participants from four continents. The top performing teams managed to segment many CoW components to Dice scores around 90%, but with lower scores for communicating arteries and rare variants. There were also topological mistakes for predictions with high Dice scores. Additional topological analysis revealed further areas for improvement in detecting certain CoW components and matching CoW variant topology accurately. TopCoW represented a first attempt at benchmarking the CoW anatomical segmentation task for MRA and CTA, both morphologically and topologically. © 2023, CC BY-NC-ND.

关键词： Large datasets

来源：评论

学校读者我要写书评

暂无评论

On the explicit feedback stabilisation of 1D linear nonautonomous parabolic equations via oblique projections

arXiv

引用

arXiv 2018年

作者： Rodrigues, Sérgio S. Sturm, Kevin Johann Radon Institute for Computational and Applied Mathematics Altenbergerstraße 69 Linz4040 Austria TU Wien Institute for Analysis and Scientific Computing Wiedner Hauptstraße 8-10 Wien1040 Austria

93D15, 47A75, 47N70In recently proposed stabilisation techniques for parabolic equations, a crucial role is played by a suitable sequence of oblique projections in Hilbert spaces, onto the linear span of a suitable set of M actuators, and along the subspace orthogonal to the space spanned by "the" first M eigenfunctions of the Laplacian operator. This new approach uses an explicit feedback law, which is stabilising provided that the sequence of operator norms of such oblique projections remains bounded. The main result of the paper is the proof that, for suitable explicitly given sequences of sets of actuators, the operator norm of the corresponding oblique projections remains bounded. In the final part of the paper we provide numerical results, showing the performance of the explicit feedback control for both Dirichlet and Neumann homogeneous boundary conditions. Copyright © 2018, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

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：