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arXiv 2019年

作者： Bilic, Patrick Christ, Patrick Li, Hongwei Bran Vorontsov, Eugene Ben-Cohen, Avi Kaissis, Georgios Szeskin, Adi Jacobs, Colin Mamani, Gabriel Efrain Humpire Chartrand, Gabriel Lohöfer, Fabian Holch, Julian Walter Sommer, Wieland Hofmann, Felix Hostettler, Alexandre Lev-Cohain, Naama Drozdzal, Michal Amitai, Michal Marianne Vivanti, Refael Sosna, Jacob Ezhov, Ivan Sekuboyina, Anjany Navarro, Fernando Kofler, Florian Paetzold, Johannes C. Shit, Suprosanna Hu, Xiaobin Lipková, Jana Rempfler, Markus Piraud, Marie Kirschke, Jan Wiestler, Benedikt Zhang, Zhiheng Hülsemeyer, Christian Beetz, Marcel Ettlinger, Florian Antonelli, Michela Bae, Woong Bellver, Míriam Bi, Lei Chen, Hao Chlebus, Grzegorz Dam, Erik B. Dou, Qi Fu, Chi-Wing Georgescu, Bogdan Giró-I-Nieto, Xavier Gruen, Felix Han, Xu Heng, Pheng-Ann Hesser, Jürgen Moltz, Jan Hendrik Igel, Christian Isensee, Fabian Jäger, Paul Jia, Fucang Kaluva, Krishna Chaitanya Khened, Mahendra Kim, Ildoo Kim, Jae-Hun Kim, Sungwoong Kohl, Simon Konopczynski, Tomasz Kori, Avinash Krishnamurthi, Ganapathy Li, Fan Li, Hongchao Li, Junbo Li, Xiaomeng Lowengrub, John Ma, Jun Maier-Hein, Klaus Maninis, Kevis-Kokitsi Meine, Hans Merhof, Dorit Pai, Akshay Perslev, Mathias Petersen, Jens Pont-Tuset, Jordi Qi, Jin Qi, Xiaojuan Rippel, Oliver Roth, Karsten Sarasua, Ignacio Schenk, Andrea Shen, Zengming Torres, Jordi Wachinger, Christian Wang, Chunliang Weninger, Leon Wu, Jianrong Xu, Daguang Yang, Xiaoping Yu, Simon Chun-Ho Yuan, Yading Yue, Miao Zhang, Liping Cardoso, Jorge Bakas, Spyridon Braren, Rickmer Heinemann, Volker Pal, Christopher Tang, An Kadoury, Samuel Soler, Luc van Ginneken, Bram Greenspan, Hayit Joskowicz, Leo Menze, Bjoern Department of Informatics Technical University of Munich Germany Department of Quantitative Biomedicine University of Zurich Switzerland Ecole Polytechnique de Montréal Canada Department of Medical Imaging Radboud University Medical Center Nijmegen Netherlands Department of Biomedical Engineering Tel-Aviv University Israel Germany Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany Philips Research China Philips China Innovation Campus Shanghai China School of Biomedical Engineering & Imaging Sciences King0s College London London United Kingdom Institute for AI in Medicine Technical University of Munich Germany Department of Computer Science Guangdong University of Foreign Studies China Institute for diagnostic and interventional radiology Klinikum rechts der Isar Technical University of Munich Germany Institute for Diagnostic and Interventional Neuroradiology Klinikum Rechts der Isar Technical University of Munich Germany Department of Hepatobiliary Surgery The Affiliated Drum Tower Hospital Nanjing University Medical School China Department of Computing Imperial College London London United Kingdom Institute for Tissue Engineering and Regenerative Medicine Helmholtz Zentrum München Neuherberg Germany Brigham and Women's Hospital Harvard Medical School United States School of Computer Science and Engineering The Hebrew University of Jerusalem Israel University of Pennsylvania PA United States Pte. Ltd. Singapore Medical Imaging and Reconstruction Lab Department of Engineering Design Indian Institute of Technology Madras India Sensetime Shanghai China Department of Radiology Perelman School of Medicine University of Pennsylvania United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PA United States Co. Ltd China MontréalQC Canada Department of Radiology Radiation Oncology and Nuclear Medicine University of Montréal

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created in collaboration with seven hospitals and research institutions. Seventy-five submitted liver and liver tumor segmentation algorithms were trained on a set of 131 computed tomography (CT) volumes and were tested on 70 unseen test images acquired from different patients. We found that not a single algorithm performed best for both liver and liver tumors in the three events. The best liver segmentation algorithm achieved a Dice score of 0.963, whereas, for tumor segmentation, the best algorithms achieved Dices scores of 0.674 (ISBI 2017), 0.702 (MICCAI 2017), and 0.739 (MICCAI 2018). Retrospectively, we performed additional analysis on liver tumor detection and revealed that not all top-performing segmentation algorithms worked well for tumor detection. The best liver tumor detection method achieved a lesion-wise recall of 0.458 (ISBI 2017), 0.515 (MICCAI 2017), and 0.554 (MICCAI 2018), indicating the need for further research. LiTS remains an active benchmark and resource for research, e.g., contributing the liver-related segmentation tasks in http://***/. In addition, both data and online evaluation are accessible via ***. © 2019, CC BY-NC-ND.

关键词： Deep learning

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On the distribution of the number of internal equilibria in random evolutionary games

arXiv

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arXiv 2017年

作者： Duong, Manh Hong Tran, Hoang Minh Han, The Anh Department of Mathematics Imperial College London LondonSW7 2AZ United Kingdom Department of Industrial and Systems Engineering Texas AandM University College StationTX77843 United States School of Applied Mathematics and Informatics Hanoi University of Science and Technology Hanoi Viet Nam School of Computing Media and Art Teeside University TS1 3BX United Kingdom

In this paper, we study the distribution of the number of internal equilibria of a multiplayer two-strategy random evolutionary game. Using techniques from the random polynomial theory, we obtain a closed formula for the probability that the game has a certain number of internal equilibria. In addition, by employing Descartes' rule of signs and combinatorial methods, we provide useful estimates for this probability. Finally, we also compare our analytical results with those obtained from samplings. Copyright © 2017, The Authors. All rights reserved.

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Hospital-coded infections in patients with cancer: Evaluating disease burden and outcomes in Australian cancer patients

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Infection, Disease & Health 2019年 24卷 S2-S2页

作者： Jake Valentine Lisa Hall Karin Verspoor Tim Spelman Leon Worth Sir Peter MacCallum Department of Oncology University of Melbourne Melbourne Australia NHMRC National Centre for Infections in Cancer Melbourne Australia Paediatric Integrated Cancer Service Parkville Australia School of Public Health University of Queensland Brisbane Australia Institute of Health and Biomedical Innovation Queensland University of Technology Brisbane Australia Health and Biomedical Informatics Centre University of Melbourne Melbourne Australia School of Computing and Information Systems University of Melbourne Melbourne Australia Department of Clinical Neuroscience Karolinska Institute Stockholm Sweden Burnet Institute for Medical Research and Public Health Melbourne Australia Victorian Healthcare Associated Infection Surveillance System Coordinating Centre Peter Doherty Institute for Infection and Immunity Melbourne Australia Department of Infectious Diseases Peter MacCallum Cancer Centre Melbourne Australia Department of Medicine University of Melbourne Melbourne Australia

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Generic anonymous identity-based broadcast encryption with chosen-ciphertext security 21st

Generic anonymous identity-based broadcast encryption with c...

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21st Australasian Conference on Information Security and Privacy, ACISP 2016

作者： He, Kai Weng, Jian Au, Man Ho Mao, Yijun Deng, Robert H. Department of Computer Science Jinan University Guangzhou China Faculty of Information Technology Monash University Melbourne Australia Department of Computing Hong Kong Polytechnic University Hong Kong School of Mathematics and Informatics South China University of Agriculture Guangzhou China School of Information Science and Technology Sun Yat-Sen University Guangzhou China School of Information Systems Singapore Management University Singapore Singapore

ISBN: (纸本)9783319403663

In a broadcast encryption system, a broadcaster can encrypt a message to a group of authorized receivers S and each authorized receiver can use his/her own private key to correctly decrypt the broadcast ciphertext, while the users outside S cannot. Identity-based broadcast encryption (IBBE) system is a variant of broadcast encryption system where any string representing the user’s identity (e.g., email address) can be used as his/her public key. IBBE has found many applications in real life, such as pay-TV systems, distribution of copyrighted materials, satellite radio communications. When employing an IBBE system, it is very important to protect the message’s confidentiality and the users’ anonymity. However, existing IBBE systems cannot satisfy confidentiality and anonymity simultaneously. In this paper, using an anonymous identity-based encryption (IBE) primitive with robust property as a building block, we propose a generic IBBE construction, which can simultaneously ensure the confidentiality and anonymity under chosenciphertext attacks. Our generic IBBE construction has a desirable property that the public parameters size, the private key size and the decryption cost are constant and independent of the number of receivers. © Springer International Publishing Switzerland 2016.

关键词： Signal receivers

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How functional programming mattered

引用

National Science Review 2015年第3期2卷 349-370页

作者： Zhenjiang Hu John Hughes Meng Wang National Institute of Informatics Department of Computer Science and Engineering Chalmers University of Technology School of Computing University of Kent Department of Informatics SOKENDAI(Graduate University for Advanced Studies)

In 1989 when functional programming was still considered a niche topic, Hughes wrote a visionary paper arguing convincingly ‘why functional programming maters’. More than two decades have passed. Has functional programming really matered? Our answer is a resounding ‘Yes!’. Functional programming is now at the forefront of a new generation of programming technologies, and enjoying increasing popularity and inluence. In this paper, we review the impact of functional programming, focusing on how it has changed the way we may construct programs, the way we may verify programs, and fundamentally the way we may think about programs.

关键词： functional programming functional languages equational reasoning monad high order function

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Interpolation of Instrument Response Functions for the Cherenkov Telescope Array in the Context of pyirf

arXiv

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arXiv 2023年

作者： Dominik, Rune Michael Linhoff, Maximilian Sitarek, Julian Abe, K. Abe, S. Acharyya, A. Adam, R. Aguasca-Cabot, A. Agudo, I. Alfaro, J. Alvarez-Crespo, N. Alves Batista, R. Amans, J.-P. Amato, E. Ambrosino, F. Angüner, E.O. Antonelli, L.A. Aramo, C. Arcaro, C. Arrabito, L. Asano, K. Aschersleben, J. Ashkar, H. Augusto Stuani, L. Baack, D. Backes, M. Balazs, C. Balbo, M. Baquero Larriva, A. Barbosa Martins, V. Barres de Almeida, U. Barrio, J.A. Bastieri, D. Batista, P.I. Batkovic, I. Batzofin, R. Baxter, J. Beck, G. Becker Tjus, J. Beiske, L. Belardinelli, D. Benbow, W. Bernardini, E. Bernete Medrano, J. Bernlöhr, K. Berti, A. Beshley, V. Bhattacharjee, P. Bhattacharyya, S. Bi, B. Biederbeck, N. Biland, A. Bissaldi, E. Blanch, O. Blazek, J. Boisson, C. Bolmont, J. Bonnoli, G. Bordas, P. Bosnjak, Z. Bradascio, F. Braiding, C. Bronzini, E. Brose, R. Brown, A.M. Brun, F. Brunelli, G. Bulgarelli, A. Burelli, I. Burmistrov, L. Burton, M. Bylund, T. Calisse, P.G. Campoy-Ordaz, A. Cantlay, B.K. Capalbi, M. Caproni, A. Capuzzo-Dolcetta, R. Carlile, C. Caroff, S. Carosi, A. Carosi, R. Carrasco, M.-S. Cascone, E. Cassol, F. Castrejon, N. Catalani, F. Cerasole, D. Cerruti, M. Chaty, S. Chen, A.W. Chernyakova, M. Chiavassa, A. Chudoba, J. Coimbra Araujo, C.H. Conforti, V. Conte, F. Contreras, J.L. Cossou, C. Costa, A. Costantini, H. Cristofari, P. Cuevas, O. Curtis-Ginsberg, Z. D'Amico, G. D'Ammando, F. Dadina, M. Dalchenko, M. David, L. Davids, I.D. Dazzi, F. De Angelis, A. de Bony de Lavergne, M. De Caprio, V. De Cesare, G. de Gouveia Dal Pino, E.M. De Lotto, B. De Lucia, M. de Menezes, R. de Naurois, M. de Ona Wilhelmi, E. De Simone, N. de Souza, V. del Peral, L. del Valle, M.V. Delagnes, E. Delgado Giler, A.G. Delgado, C. Dell'aiera, M. Della Ceca, R. Della Valle, M. della Volpe, D. Depaoli, D. Dettlaff, A. Di Girolamo, T. Di Piano, A. Di Pierro, F. Di Tria, R. Di Venere, L. Díaz-Bahamondes, C. Dib, C. Diebold, S. Dima, R. Dinesh, A. Djannati-Ataï, A. Djuvsland, J. TU Dortmund University Department of Physics Otto-Hahn-Straße 4a D-44227 Germany University of Lodz Faculty of Physics and Applied Informatics Pomorska 149/153 Lodz90-236 Poland Department of Physics Tokai University 4-1-1 Kita-Kaname Kanagawa Hiratsuka259-1292 Japan Institute for Cosmic Ray Research University of Tokyo 5-1-5 Kashiwa-no-ha Chiba Kashiwa277-8582 Japan University of Alabama Tuscaloosa Department of Physics and Astronomy Gallalee Hall Box 870324 TuscaloosaAL35487-0324 United States Université Côte d'Azur Observatoire de la Côte d'Azur CNRS Laboratoire Lagrange France Laboratoire Leprince-Ringuet CNRS IN2P3 École polytechnique Institut Polytechnique de Paris Palaiseau91120 France Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Martí i Franquès 1 Barcelona08028 Spain Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain Pontificia Universidad Católica de Chile Av. Libertador Bernardo O'Higgins 340 Santiago Chile IPARCOS-UCM Instituto de Física de Partículas y del Cosmos EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain Instituto de Física Teórica UAM CSIC Departamento de Física Teórica Universidad Autónoma de Madrid c/Nicolás Cabrera 13-15 Campus de Cantoblanco UAM Madrid28049 Spain LUTH GEPI and LERMA Observatoire de Paris Université PSL Université Paris Cité CNRS 5 place Jules Janssen Meudon92190 France INAF - Osservatorio Astrofisico di Arcetri Largo E. Fermi 5 Firenze50125 Italy INAF - Osservatorio Astronomico di Roma Via di Frascati 33 Monteporzio Catone00040 Italy TÜBİTAK Research Institute for Fundamental Sciences Gebze Kocaeli41470 Turkey INFN Sezione di Napoli Via Cintia ed. G Napoli80126 Italy INFN Sezione di Padova Via Marzolo 8 Padova35131 Italy Laboratoire Univers et Particules de Montpellier Université de Montpellier CNRS IN2P3 CC 72 Place Eugène Bataillon Montp

The Cherenkov Telescope Array (CTA) will be the next generation ground-based very-high-energy gamma-ray observatory, constituted by tens of Imaging Atmospheric Cherenkov Telescopes at two sites once its construction and commissioning are finished. Like its predecessors, CTA relies on Instrument Response Functions (IRFs) to relate the observed and reconstructed properties to the true ones of the primary gamma-ray photons. IRFs are needed for the proper reconstruction of spectral and spatial information of the observed sources and are thus among the data products issued to the observatory users. They are derived from Monte Carlo simulations, depend on observation conditions like the telescope pointing direction or the atmospheric transparency and can evolve with time as hardware ages or is replaced. Producing a complete set of IRFs from simulations for every observation taken is a time-consuming task and not feasible when releasing data products on short timescales. Consequently, interpolation techniques on simulated IRFs are investigated to quickly estimate IRFs for specific observation conditions. However, as some of the IRFs constituents are given as probability distributions, specialized methods are needed. This contribution summarizes and compares the feasibility of multiple approaches to interpolate IRF components in the context of the pyirf python software package and IRFs simulated for the Large-Sized Telescope prototype (LST-1). We will also give an overview of the current functionalities implemented in pyirf. © 2023, CC BY-NC-ND.

关键词： Python

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A Telemedicine Application Using WebRTC

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Procedia Computer Science 2016年 100卷 414-420页

作者： Mário Antunes Catarina Silva Joaquim Barranca School of Technology and Management Polytechnic Institute of Leiria Portugal Center for Research in Advanced Computing Systems INESC-TEC University of Porto Portugal Center for Informatics and Systems of the University of Coimbra Portugal

ICT in healthcare businesses has been growing in Portugal in the past few decades. The implementation of large scale information systems in hospitals, the deployment of electronic prescription and electronic patient records applications are just a few examples. Telemedicine is another emergent and widely used ICT solution to smooth the communication between patients and healthcare professionals, by allowing video and voice transfer over the Internet. Although there are several implementations of telemedicine solutions, they usually have some drawbacks, namely: i) too specific for a purpose; ii) based on proprietary applications; iii) require additional software installation; iv) and usually have associated costs. In this paper we propose a telemedicine solution based on WebRTC Application Programming Interface (API) to transmit video and voice in real time over the Internet, through a web browser. Besides microphone and webcam control, we have also included two additional functionalities that may be useful to both patients and healthcare professionals during the communication, namelyi) bidirectional sending files capability and ii) shared whiteboard which allows free drawing. The proposed solution uses exclusively open source software components and requires solely a WebRTC compatible web browser, like Google Chrome or Firefox. We have made two types of tests in healthcare environment: i) a bidirectional patient-doctor communication; ii) and connecting at one end an external USB medical device with an integrated webcam. The results were promising, since they revealed the potential of using WebRTC API to control microphone and webcam in a telemedicine application, as well as the appropriateness and acceptance of the features included.

关键词： eHealth Telemedicine WebRTC: Healthcare

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Efficient Priority Packet Recovery Based on Network Coding in DVB-IPDC System

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China Communications 2015年第7期12卷 167-178页

作者： WANG Lian PENG Daiyuan LIANG Hongbin Provincial Key Laboratory of Information Coding and Transmission School of Information Science and TechnologySouthwest Jiaotong University College of Computing Science and Technology Chongqing University of Posts and Telecommunications School of Transportation and Logistics Southwest Jiaotong University Secure Networking and Computing Institute School of Computing Informatics and Decision Systems EngineeringArizona State University

In DVB-IPDC system, due to the constraints of handheld devices and the broadcast nature of wireless network, packet loss is inevitable. ECDR-NC proposed is a retransmission encoding packet selection algorithm based on the dynamic information updating, which can find the current most effective complete decoding packet. ECDR-NC can not only avoid the redundant encoding packets due to the overlapping among encoding packets, but also reduce the computational complexity compared with the traditional encoding schemes. Furthermore, the retransmission upper bound of ECDR-NC is fully controlled. In time-sensitive applications, to maximize the aggregate number of recovery packets while minimizing the total number of discarded packets due to the time limit according to the priority preference, the adaptive priority scheme EPNC is formulized, and the weighted relation graph is constructed to find the maximum-weighted encoding packets sequence according to the decoding gains. In the same network environment, the performances comparisons between PNC and EPNC show that EPNC is more efficient and more rational, and the average discarded packets ratios ofEPNC can be reduced about 18%~27%. The main contributions of this paper are an effective retransmission encoding packet selection algorithm ECDR-NC proposed, and a new adaptive priority recovery scheme EPNC introduced into DVB-IPDC system.

关键词： digital video broadcasting（DVB） retransmission network coding（NC） longterm evolution（LTE） wireless network

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Determinants of next generation e-Health network and architecture specifications

Determinants of next generation e-Health network and archite...

引用

International Conference on e-health Networking, Applications and Services (HealthCom)

作者： Christoph Thuemmler Alois Paulin Ai Keow Lim School of Computing Edinburgh Napier University Edinburgh UK Faculty of Informatics Vienna University of Technology Vienna Austria Celestor Ltd Edinburgh UK

ISBN: (纸本)9781509033713

This paper summarizes the determinants for future e-Health network and IT infrastructures in the health care environment. The paper bases on observations conducted as part of a larger study at a university hospital in Munich, and summarizes ongoing discussions, key determinants from relevant whire papers, and challenges of the domain. The objective of the paper is to provide a broad overview over the implications of the e-Health domain to provide inputs in ongoing discussion on 5G characteristics.

关键词： medical computing health care medical computing Determinants Health Care Public Health university hospital INFRASTRUCTURE paper Specifications

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Large-scale collaborative imaging genetics studies of risk genetic factors for Alzheimer’s disease across multiple institutions 1st

Large-scale collaborative imaging genetics studies of risk g...

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1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2016

作者： Li, Qingyang Yang, Tao Zhan, Liang Hibar, Derrek Paul Jahanshad, Neda Wang, Yalin Ye, Jieping Thompson, Paul M. Wang, Jie School of Computing Informaticsand Decision Systems Engineering Arizona State University TempeAZ United States Department of Engineering and Technology University of Wisconsin-Stout MenomonieWI United States Imaging Genetics Center Institute for Neuroimaging and Informatics University of Southern California Marina del ReyCA United States Department of Computational Medicine and Bioinformatics University of Michigan Ann ArborMI United States

ISBN: (纸本)9783319467191

Genome-wide association studies (GWAS) offer new opportunities to identify genetic risk factors for Alzheimer’s disease (AD). Recently,collaborative efforts across different institutions emerged that enhance the power of many existing techniques on individual institution data. However,a major barrier to collaborative studies of GWAS is that many institutions need to preserve individual data privacy. To address this challenge,we propose a novel distributed framework,termed Local Query Model (LQM) to detect risk SNPs for AD across multiple research institutions. To accelerate the learning process,we propose a Distributed Enhanced Dual Polytope Projection (D-EDPP) screening rule to identify irrelevant features and remove them from the optimization. To the best of our knowledge,this is the first successful run of the computationally intensive model selection procedure to learn a consistent model across different institutions without compromising their privacy while ranking the SNPs that may collectively affect AD. Empirical studies are conducted on 809 subjects with 5.9 million SNP features which are distributed across three individual institutions. D-EDPP achieved a 66-fold speed-up by effectively identifying irrelevant features. © Springer International Publishing AG 2016.

关键词： Data privacy

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