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Fully Automatic Initialization and Segmentation of Left and Right Ventricles for Large-Scale Cardiac MRI Using a Deeply Supervised Network and 3D-ASM

SSRN

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SSRN 2023年

作者： Hu, Huaifei Pan, Ning Frangi, Alejandro F. College of Biomedical Engineering South-Central Minzu University Wuhan430074 China Hubei Key Laboratory of Medical Information Analysis and Tumor Diagnosis & Treatment Wuhan430074 China Key Laboratory of Cognitive Science State Ethnic Affairs Commission Wuhan430074 China School of Computing University of Leeds Leeds United Kingdom School of Medicine University of Leeds Leeds United Kingdom Medical Imaging Research Centre Cardiovascular Sciences Department KU Leuven Leuven Belgium Medical Imaging Research Centre Electrical Engineering Department KU Leuven Leuven Belgium

Background and objective: The sheer volume of data generated by population imaging studies is unparalleled by current capabilities to extract objective and quantitative cardiac phenotypes;subjective and time-consuming manual image analysis remains the gold standard. Automated image analytics to compute quantitative imaging biomarkers of cardiac function are desperately needed. Data volumes and their variability pose a challenge to most state-of-the-art methods for endo and epicardial contours, which lack robustness when applied to very large datasets. Our aim is to develop an analysis pipeline for the automatic quantification of cardiac function from cine magnetic resonance imaging ***: This work adopt 4,638 cardiac MRI cases coming from UK Biobank with ground truth available for left and RV contours. A hybrid and robust algorithm is proposed to improve the accuracy of automatic left and right ventricle segmentation by harnessing the localization accuracy of deep learning and the morphological accuracy of 3D-ASM (three-dimensional active shape models). The contributions of this paper are three-fold. First, a fully automatic method is proposed for left and right ventricle initialization and cardiac MRI segmentation by taking full advantage of spatiotemporal constraint. Second, a deeply supervised network is introduced to train and segment the heart. Third, the 3D-ASM image search procedure is improved by combining image intensity models with convolutional neural network (CNN) derived distance maps improving endo- and epicardial edge ***: The proposed architecture outperformed the state of the art for cardiac MRI segmentation from UK Biobank. The statistics of RV landmarks detection errors for Triscuspid valve and RV apex are 4.17 mm and 5.58 mm separately. The overlap metric, mean contour distance, Hausdorff distance and cardiac functional parameters are calculated for the LV (Left Ventricle) and RV (Right Ventricle) contour segmentations. Bl

关键词： Heart

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THE GLOBAL ATTRACTOR FOR A VISCOUS WEAKLY DISSIPATIVE GENERALIZED TWO-COMPONENT μ-HUNTER-SAXTON SYSTEM

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Acta Mathematica Scientia 2018年第2期38卷 651-672页

作者：张磊刘斌 School of Mathematics and Statistics Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology

This article is concerned with the existence of global attractor of a weakly dissipative generalized two-component μ-Hunter-Saxton （gμHS2） system with viscous terms. Under the period boundary conditions and with the help of the Galerkin procedure and compactness method, we first investigate the existence of global solution for the viscous weakly dissipative （gμHS2） system. On the basis of some uniformly prior estimates of the solution to the viscous weakly dissipative （gμHS2） system, we show that the semi-group of the solution operator {S（t）}t≥0 has a bounded absorbing set. Moreover, we prove that the dynamical system {S（t）}t≥0 possesses a global attractor in the Sobolev space H2（S） × H2（S）.

关键词： Generalized two-component μ-Hunter-Saxton system viscous weakly dissipative existence global attractor period boundary conditions

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Phase-field-based lattice Boltzmann model for immiscible incompressible N-phase flows

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Physical Review E 2020年第6期101卷 063310-063310页

作者： Xiaolei Yuan Hong Liang Zhenhua Chai Baochang Shi School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan 430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan 430074 China Department of Physics Hangzhou Dianzi University Hangzhou 310018 China

In this paper, we develop an efficient and alternative lattice Boltzmann (LB) model for simulating immiscible incompressible N-phase flows (N≥2) based on the Cahn-Hilliard phase field theory. In order to facilitate the design of LB model and reduce the calculation of the gradient term, the governing equations of the N-phase system are reformulated, and they satisfy the conservation of mass, momentum and the second law of thermodynamics. In the present model, (N−1) LB equations are employed to capture the interface, and another LB equation is used to solve the Navier-Stokes (N-S) equations, where a new distribution function for the total force is delicately designed to reduce the calculation of the gradient term. The developed model is first validated by two classical benchmark problems, including the tests of static droplets and the spreading of a liquid lens, the simulation results show that the current LB model is accurate and efficient for simulating incompressible N-phase fluid flows. To further demonstrate the capability of the LB model, two numerical simulations, including dynamics of droplet collision for four fluid phases and dynamics of droplets and interfaces for five fluid phases, are performed to test the developed model. The results show that the present model can successfully handle complex interactions among N (N≥2) immiscible incompressible flows.

关键词： Multiphase flows Lattice-Boltzmann methods

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Discrete unified gas kinetic scheme for nonlinear convection-diffusion equations

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Physical Review E 2020年第2期101卷 023306-023306页

作者： Jinlong Shang Zhenhua Chai Huili Wang Baochang Shi School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan 430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan 430074 China School of Mathematics and Computer Science Wuhan Textile University Wuhan 430073 China

In this paper, we develop a discrete unified gas kinetic scheme (DUGKS) for a general nonlinear convection-diffusion equation (NCDE) and show that the NCDE can be recovered correctly from the present model through the Chapman-Enskog analysis. We then test the present DUGKS through some classic convection-diffusion equations, and we find that the numerical results are in good agreement with analytical solutions and that the DUGKS model has a second-order convergence rate. Finally, as a finite-volume method, the DUGKS can also adopt the nonuniform mesh. Besides, we perform some comparisons among the DUGKS, the finite-volume lattice Boltzmann model (FV-LBM), the single-relaxation-time lattice Boltzmann model (SLBM), and the multiple-relaxation-time lattice Boltzmann model (MRT-LBM). The results show that the present DUGKS is more accurate than the FV-LBM, more stable than the SLBM, and almost has the same accuracy as the MRT-LBM. Moreover, the use of nonuniform mesh may make the DUGKS model more flexible.

关键词： Lattice-Boltzmann methods

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TVIDS: Trusted Virtual IDS With SGX

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China Communications 2019年第10期16卷 133-150页

作者： Juan Wang Shirong Hao Yi Li Zhi Hong Fei Yan Bo Zhao Jing Ma Huanguo Zhang Key Laboratory of Aerospace Information Security and Trust Computing Ministry of EducationSchool of Cyber Science and EngineeringWuhan UniversityWuhan 430072HubeiChina School of Cyber Science and Engineering Wuhan UniversityWuhan 430072China Science and Technology on Information Assurance Laboratory Beijing 100072China

Network functions such as intrusion detection systems (IDS) have been increasingly deployed as virtual network functions or outsourced to cloud service providers so as to achieve the scalability and agility, and reducing equipment costs and operational cost. However, virtual intrusion detection systems (VIDS) face more serious security threats due to running in a shared and virtualized environment instead of proprietary devices. Cloud service providers or malicious tenants may illegally access and tamper with the policies, packet information, and internal processing states of intrusion detection systems, thereby violating the privacy and security of tenant’s networks. To address these challenges, we use Intel Software Guard Extensions (SGX) to build a Trusted Virtual Intrusion Detection System (TVIDS). For TVIDS, to prevent cloud service providers from accessing sensitive information about the users’ network, we build a trusted execution environment for security policy, packets processing, and internal state so that cloud service providers and other malicious tenants can’t access the protected code, policy, processing states, and packets information of the intrusion detection system. We implemented TVIDS on the basis of the Snort which is a famous open-source IDS and evaluated its results on real SGX *** results show that our method can protect the security of the virtual IDS and brings acceptable performance overhead.

关键词： network function virtualization intrusion detection system SGX trusted execution environment

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How much faster does the best polynomial approximation converge than Legendre projection?

arXiv

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arXiv 2020年

作者： Wang, Haiyong School of Mathematics and Statistics Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Engineering Modeling and Scientific Computing Huazhong University of Science and Technology Wuhan430074 China

We compare the convergence behavior of best polynomial approximations and Legendre and Chebyshev projections and derive optimal rates of convergence of Legendre projections for analytic and differentiable functions in the maximum norm. For analytic functions, we show that the best polynomial approximation of degree n is better than the Legendre projection of the same degree by a factor of n1/2. For differentiable functions such as piecewise analytic functions and functions of fractional smoothness, however, we show that the best approximation is better than the Legendre projection by only some constant factors. Our results provide some new insights into the approximation power of Legendre projections. Copyright © 2020, The Authors. All rights reserved.

关键词： Functions

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Optimal rates of convergence and error localization of Gegenbauer projections

arXiv

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arXiv 2020年

Motivated by comparing the convergence behavior of Gegenbauer projections and best approximations, we study the optimal rate of convergence for Gegenbauer projections in the maximum norm. We show that the rate of convergence of Gegenbauer projections is the same as that of best approximations under conditions of the underlying function is either analytic on and within an ellipse and λ ≤ 0 or differentiable and λ ≤ 1, where λ is the parameter in Gegenbauer projections. If the underlying function is analytic and λ > 0 or differentiable and λ > 1, then the rate of convergence of Gegenbauer projections is slower than that of best approximations by factors of nλ and nλ−1, respectively. An exceptional case is functions with endpoint singularities, for which Gegenbauer projections and best approximations converge at the same rate for all λ > −1/2. For functions with interior or endpoint singularities, we provide a theoretical explanation for the error localization phenomenon of Gegenbauer projections and for why the accuracy of Gegenbauer projections is better than that of best approximations except in small neighborhoods of the critical points. Our analysis provides fundamentally new insight into the power of Gegenbauer approximations and related spectral *** Codes 41A10, 41A25 Copyright © 2020, The Authors. All rights reserved.

关键词： Functions

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Optical Flow for Video Super-Resolution: A Survey

arXiv

引用

arXiv 2022年

作者： Tu, Zhigang Li, Hongyan Xie, Wei Liu, Yuanzhong Zhang, Shifu Li, Baoxin Yuan, Junsong State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University China School of Information Engineering Hubei University of Economics Wuhan China School of Computer Central China Normal University Wuhan China School of Computing Informatics Decision System Engineering Arizona State University United States Computer Science and Engineering Department State University of New York Buffalo United States

Video super-resolution is currently one of the most active research topics in computer vision as it plays an important role in many visual applications. Generally, video super-resolution contains a significant component, i.e., motion compensation, which is used to estimate the displacement between successive video frames for temporal alignment. Optical flow, which can supply dense and sub-pixel motion between consecutive frames, is among the most common ways for this task. To obtain a good understanding of the effect that optical flow acts in video super-resolution, in this work, we conduct a comprehensive review on this subject for the first time. This investigation covers the following major topics: the function of super-resolution (i.e., why we require super-resolution);the concept of video super-resolution (i.e., what is video super-resolution);the description of evaluation metrics (i.e., how (video) superresolution performs);the introduction of optical flow based video super-resolution;the investigation of using optical flow to capture temporal dependency for video super-resolution. Prominently, we give an in-depth study of the deep learning based video super-resolution method, where some representative algorithms are analyzed and compared. Additionally, we highlight some promising research directions and open issues that should be further addressed. © 2022, CC BY.

关键词： Optical flows

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Stringent Tests of Lorentz Invariance Violation from LHAASO Observations of GRB 221009A

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Physical Review Letters 2024年第7期133卷 071501-071501页

作者： Zhen Cao F. Aharonian Axikegu Y. X. Bai Y. W. Bao D. Bastieri X. J. Bi Y. J. Bi W. Bian A. V. Bukevich Q. Cao W. Y. Cao Zhe Cao J. Chang J. F. Chang A. M. Chen E. S. Chen H. X. Chen Liang Chen Lin Chen Long Chen M. J. Chen M. L. Chen Q. H. Chen S. Chen S. H. Chen S. Z. Chen T. L. Chen Y. Chen N. Cheng Y. D. Cheng M. Y. Cui S. W. Cui X. H. Cui Y. D. Cui B. Z. Dai H. L. Dai Z. G. Dai Danzengluobu X. Q. Dong K. K. Duan J. H. Fan Y. Z. Fan J. Fang J. H. Fang K. Fang C. F. Feng H. Feng L. Feng S. H. Feng X. T. Feng Y. Feng Y. L. Feng S. Gabici B. Gao C. D. Gao Q. Gao W. Gao W. K. Gao M. M. Ge L. S. Geng G. Giacinti G. H. Gong Q. B. Gou M. H. Gu F. L. Guo X. L. Guo Y. Q. Guo Y. Y. Guo Y. A. Han M. Hasan H. H. He H. N. He J. Y. He Y. He Y. K. Hor B. W. Hou C. Hou X. Hou H. B. Hu Q. Hu S. C. Hu D. H. Huang T. Q. Huang W. J. Huang X. T. Huang X. Y. Huang Y. Huang X. L. Ji H. Y. Jia K. Jia K. Jiang X. W. Jiang Z. J. Jiang M. Jin M. M. Kang I. Karpikov D. Kuleshov K. Kurinov B. B. Li C. M. Li Cheng Li Cong Li D. Li F. Li H. B. Li H. C. Li Jian Li Jie Li K. Li S. D. Li W. L. Li X. R. Li Xin Li Y. Z. Li Zhe Li Zhuo Li E. W. Liang Y. F. Liang S. J. Lin B. Liu C. Liu D. Liu D. B. Liu H. Liu H. D. Liu J. Liu J. L. Liu M. Y. Liu R. Y. Liu S. M. Liu W. Liu Y. Liu Y. N. Liu Q. Luo Y. Luo H. K. Lv B. Q. Ma L. L. Ma X. H. Ma J. R. Mao Z. Min W. Mitthumsiri H. J. Mu Y. C. Nan A. Neronov L. J. Ou P. Pattarakijwanich Z. Y. Pei J. C. Qi M. Y. Qi B. Q. Qiao J. J. Qin A. Raza D. Ruffolo A. Sáiz M. Saeed D. Semikoz L. Shao O. Shchegolev X. D. Sheng F. W. Shu H. C. Song Yu. V. Stenkin V. Stepanov Y. Su D. X. Sun Q. N. Sun X. N. Sun Z. B. Sun J. Takata P. H. T. Tam Q. W. Tang R. Tang Z. B. Tang W. W. Tian C. Wang C. B. Wang G. W. Wang H. G. Wang H. H. Wang J. C. Wang Kai Wang L. P. Wang L. Y. Wang P. H. Wang R. Wang W. Wang X. G. Wang X. Y. Wang Y. Wang Y. D. Wang Y. J. Wang Z. H. Wang Z. X. Wang Zhen Wang Zheng Wang D. M. Wei J. J. Wei Y. J. Wei T. Wen C. Y. Wu H. R. Wu Q. W. Wu S. Wu X. F. Wu Y. S. Wu S. Q. Xi J. Xia G. M. Xiang D. X. Xiao Key Laboratory of Particle Astrophysics and Experimental Physics Division and Computing Center Institute of High Energy Physics Chinese Academy of Sciences 100049 Beijing China University of Chinese Academy of Sciences 100049 Beijing China Tianfu Cosmic Ray Research Center 610000 Chengdu Sichuan China Dublin Institute for Advanced Studies 31 Fitzwilliam Place 2 Dublin Ireland Max-Planck-Institut for Nuclear Physics P.O. Box 103980 69029 Heidelberg Germany School of Physical Science and Technology and School of Information Science and Technology Southwest Jiaotong University 610031 Chengdu Sichuan China School of Astronomy and Space Science Nanjing University 210023 Nanjing Jiangsu China Center for Astrophysics Guangzhou University 510006 Guangzhou Guangdong China Tsung-Dao Lee Institute and School of Physics and Astronomy Shanghai Jiao Tong University 200240 Shanghai China Institute for Nuclear Research of Russian Academy of Sciences 117312 Moscow Russia Hebei Normal University 050024 Shijiazhuang Hebei China University of Science and Technology of China 230026 Hefei Anhui China State Key Laboratory of Particle Detection and Electronics China Key Laboratory of Dark Matter and Space Astronomy and Key Laboratory of Radio Astronomy Research Center for Astronomical Computing Zhejiang Laboratory 311121 Hangzhou Zhejiang China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical Observatory Chinese Academy of Sciences 200030 Shanghai China School of Physics and Astronomy Yunnan University 650091 Kunming Yunnan China Key Laboratory of Cosmic Rays (Tibet University) Ministry of Education 850000 Lhasa Tibet China National Astronomical Observatories Chinese Academy of Sciences 100101 Beijing China School of Physics and Astronomy (Zhuhai) and School of Physics (Guangzhou) and Sino-French Institute of Nuclear Engineering and Technology (Zhuhai) Sun Yat-sen University 519000 Zhuhai and 510275 Guangzhou Guangdong China Institute of Frontier a

On 9 October 2022, the Large High Altitude Air Shower Observatory (LHAASO) reported the observation of the very early TeV afterglow of the brightest-of-all-time gamma-ray burst 221009A, recording the highest photon statistics in the TeV band ever obtained from a gamma-ray burst. We use this unique observation to place stringent constraints on the energy dependence of the speed of light in vacuum, a manifestation of Lorentz invariance violation (LIV) predicted by some quantum gravity (QG) theories. Our results show that the 95% confidence level lower limits on the QG energy scales are EQG,1>10 times the Planck energy EPl for the linear LIV effect, and EQG,2>6×10−8EPl for the quadratic LIV effect. Our limits on the quadratic LIV case improve previous best bounds by factors of 5–7.

关键词： Gamma ray bursts Gravitation Quantum gravity

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Majorana polarization in non-Hermitian topological superconductors

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Physical Review B 2021年第13期103卷 134507-134507页

作者： Zhen-Hua Wang Fuming Xu Lin Li Dong-Hui Xu Wei-Qiang Chen Bin Wang Shenzhen Key Laboratory of Advanced Thin Films and Applications College of Physics and Optoelectronic Engineering Shenzhen University Shenzhen 518060 China Center for Quantum Computing Peng Cheng Laboratory Shenzhen 518055 China College of Physics and Electronic Engineering and Center for Computational Sciences Sichuan Normal University Chengdu 610068 China Department of Physics Hubei University Wuhan 430062 China Department of Physics and Shenzhen Key Laboratory of Advanced Quantum Functional Materials and Devices Southern University of Science and Technology Shenzhen 518055 China Institute for Quantum Science and Engineering Southern University of Science and Technology Shenzhen 518055 China

Topological invariants play an important role in characterizing topological phases. However, the topological invariants of Hermitian systems usually fail to characterize non-Hermitian topological systems due to non-Hermiticity. In this work, we generalize the Majorana polarization, which is initially defined to describe Hermitian topological superconductors, as a topological edge invariant to characterize the non-Hermitian topological superconductors. The definition of the generalized Majorana polarization depends upon two inequivalent particle-hole symmetries in non-Hermitian systems. The spinless Kitaev chain model and topological superconductor model on the honeycomb lattice are considered to examine the reliability and validity of the generalized Majorana polarization. We find that the phase transitions obtained by using Majorana polarization are consistent with the commonly used complex-energy point gap descriptions, which indicates the Majorana polarization is a reliable topological invariant to characterize the topological phase transition in non-Hermitian topological superconductors. In addition, the non-Hermitian skin effect on Majorana bound states in non-Hermitian topological superconductors is also discussed.

关键词： Majorana bound states Skin effect Topological phase transition Honeycomb lattice Kitaev model Tight-binding model

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