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Coarse-to-Fine Learning for Single-Image Super-Resolution

IEEE Transactions on Neural Networks and Learning systems 2017年第5期28卷 1109-1122页

作者： Zhang, Kaibing Tao, Dacheng Gao, Xinbo Li, Xuelong Li, Jie School of Computer and Information Science Hubei Engineering University Xiaogan Hubei432000 China Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway Street UltimoNSW2007 Australia State Key Laboratory of Integrated Services Networks School of Electronic Engineering Xidian University Xi'an Shaanxi710071 China State Key Laboratory of Transient Optics and Photonics Xi'An Institute of Optics and Precision Mechanics Chinese Academy of Sciences Xi'an Shaanxi710119 China Video and Image Processing System Laboratory School of Electronic Engineering Xidian University Xi'an Shaanxi710071 China

This paper develops a coarse-to-fine framework for single-image super-resolution (SR) reconstruction. The coarse-to-fine approach achieves high-quality SR recovery based on the complementary properties of both example learning-and reconstruction-based algorithms: example learning-based SR approaches are useful for generating plausible details from external exemplars but poor at suppressing aliasing artifacts, while reconstruction-based SR methods are propitious for preserving sharp edges yet fail to generate fine details. In the coarse stage of the method, we use a set of simple yet effective mapping functions, learned via correlative neighbor regression of grouped low-resolution (LR) to high-resolution (HR) dictionary atoms, to synthesize an initial SR estimate with particularly low computational cost. In the fine stage, we devise an effective regularization term that seamlessly integrates the properties of local structural regularity, nonlocal self-similarity, and collaborative representation over relevant atoms in a learned HR dictionary, to further improve the visual quality of the initial SR estimation obtained in the coarse stage. The experimental results indicate that our method outperforms other state-of-the-art methods for producing high-quality images despite that both the initial SR estimation and the followed enhancement are cheap to implement. © 2012 IEEE.

关键词： Optical resolving power

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LifeTime and improving European healthcare through cell-based interceptive medicine (vol 587, pg 377, 2020)

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NATURE 2021年第7852期592卷 E8-E8页

作者： Rajewsky, Nikolaus Almouzni, Genevieve Gorski, Stanislaw A. Aerts, Stein Amit, Ido Bertero, Michela G. Bock, Christoph Bredenoord, Annelien L. Cavalli, Giacomo Chiocca, Susanna Clevers, Hans De Strooper, Bart Eggert, Angelika Ellenberg, Jan Fernandez, Xose M. Figlerowicz, Marek Gasser, Susan M. Hubner, Norbert Kjems, Jorgen Knoblich, Jurgen A. Krabbe, Grietje Lichter, Peter Linnarsson, Sten Marine, Jean-Christophe Marioni, John C. Marti-Renom, Marc A. Netea, Mihai G. Nickel, Dorthe Nollmann, Marcelo Novak, Halina R. Parkinson, Helen Piccolo, Stefano Pinheiro, Ines Pombo, Ana Popp, Christian Reik, Wolf Roman-Roman, Sergio Rosenstiel, Philip Schultze, Joachim L. Stegle, Oliver Tanay, Amos Testa, Giuseppe Thanos, Dimitris Theis, Fabian J. Torres-Padilla, Maria-Elena Valencia, Alfonso Vallot, Celine van Oudenaarden, Alexander Vidal, Marie Voet, Thierry Berlin Institute for Medical Systems Biology Max Delbrück Center for Molecular Medicine in the Helmholtz Association Berlin Germany Charité-Universitätsmedizin Berlin Germany Berlin Institute of Health (BIH) Berlin Germany German Center for Cardiovascular Research (DZHK) Partner Site Berlin Berlin Germany Institute for Biology Humboldt University of Berlin Berlin Germany Cardiovascular and Metabolic Sciences Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC) Berlin Germany Department of Pediatric Oncology/Hematology Charité-Universitätsmedizin Berlin Berlin Germany Institut Curie CNRS PSL Research University Sorbonne Université Nuclear Dynamics Unit Equipe Labellisée Ligue contre le cancer Paris France VIB Center for Brain and Disease Research Leuven Belgium Department of Human Genetics KU Leuven Leuven Belgium Department of Neurosciences KU Leuven Leuven Belgium UK Dementia Research Institute at UCL University College London London UK Wellcome Sanger Institute Wellcome Genome Campus Cambridge UK Department of Immunology Weizmann Institute of Science Rehovot Israel Centre for Genomic Regulation (CRG) Barcelona Institute of Science and Technology Barcelona Spain CNAG-CRG Centre for Genomic Regulation Barcelona Institute of Science and Technology Barcelona Spain Universitat Pompeu Fabra Barcelona Spain ICREA Barcelona Spain CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences Vienna Austria Department of Laboratory Medicine Medical University of Vienna Vienna Austria Ludwig Boltzmann Institute for Rare and Undiagnosed Diseases Vienna Austria Department of Medical Humanities Julius Center for Health Sciences and Primary Care University Medical Center Utrecht Utrecht The Netherlands Institute of Human Genetics UMR 9002 CNRS and University of Montpellier Montpellier France Department of Experimental Oncology IEO European Institute of Oncology IRCCS Milan Italy Department of Oncology and Hemato

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Understanding and Predicting Trends in Urban Freight Transport

Understanding and Predicting Trends in Urban Freight Transpo...

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International Conference on Mobile Data Management

作者： Petar Mrazovic Bahaeddin Eravci Josep Lluis Larriba-Pey Hakan Ferhatosmanoglu Mihhail Matskin Dept. of Software and Computer Systems Royal Institute of Technology Stockholm Sweden Dept. of Computer Engineering Bilkent University Ankara Turkey Dept. of Computer Architecture Polytechnic University of Catalonia Barcelona Spain Max Planck Institute for Informatics Saarbruecken Germany

ISBN: (纸本)9781538639337

Among different components of urban mobility, urban freight transport is usually considered as the least sustainable. Limited traffic infrastructures and increasing demands in dense urban regions lead to frequent delivery runs with smaller freight vehicles. This increases the traffic in urban areas and has negative impacts upon the quality of life in urban populations. Data driven optimizations are essential to better utilize existing urban transport infrastructures and to reduce the negative effects of freight deliveries for the cities. However, there is limited work and data driven research on urban delivery areas and freight transportation networks. In this paper, we collect and analyse data on urban freight deliveries and parking areas towards an optimized urban freight transportation system. Using a new check-in based mobile parking system for freight vehicles, we aim to understand and optimize freight distribution processes. We explore the relationship between areas' availability patterns and underlying traffic behaviour in order to understand the trends in urban freight transport. By applying the detected patterns we predict the availabilities of loading/unloading areas, and thus open up new possibilities for delivery route planning and better managing of freight transport infrastructures.

关键词： Loading Urban areas Mobile communication Market research Mobile applications Sociology Statistics

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Global investments in pandemic preparedness and COVID-19: development assistance and domestic spending on health between 1990 and 2026

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The Lancet Global Health 2023年第3期11卷 e385-e413页

作者： Micah, Angela E. Bhangdia, Kayleigh Cogswell, Ian E. Lasher, Dylan Lidral-Porter, Brendan Maddison, Emilie R. Nguyen, Trang Nhu Ngoc Patel, Nishali Pedroza, Paola Solorio, Juan Stutzman, Hayley Tsakalos, Golsum Wang, Yifeng Warriner, Wesley Zhao, Yingxi Zlavog, Bianca S. Abbafati, Cristiana Abbas, Jaffar Abbasi-Kangevari, Mohsen Abbasi-Kangevari, Zeinab Abdelmasseh, Michael Abdulah, Deldar Morad Abedi, Aidin Abegaz, Kedir Hussein Abhilash, E.S. Aboagye, Richard Gyan Abolhassani, Hassan Abrigo, Michael R.M. Abubaker Ali, Hiwa Abu-Gharbieh, Eman Adem, Mohammed Hussien Afzal, Muhammad Sohail Ahmadi, Ali Ahmed, Haroon Ahmed Rashid, Tarik Aji, Budi Akbarialiabad, Hossein Akelew, Yibeltal Al Hamad, Hanadi Alam, Khurshid Alanezi, Fahad Mashhour Alanzi, Turki M. Al-Hanawi, Mohammed Khaled Alhassan, Robert Kaba Aljunid, Syed Mohamed Almustanyir, Sami Al-Raddadi, Rajaa M. Alvis-Guzman, Nelson Alvis-Zakzuk, Nelson J. Amare, Azmeraw T. Ameyaw, Edward Kwabena Amini-Rarani, Mostafa Amu, Hubert Ancuceanu, Robert Andrei, Tudorel Anwar, Sumadi Lukman Appiah, Francis Aqeel, Muhammad Arabloo, Jalal Arab-Zozani, Morteza Aravkin, Aleksandr Y. Aremu, Olatunde Aruleba, Raphael Taiwo Athari, Seyyed Shamsadin Avila-Burgos, Leticia Ayanore, Martin Amogre Azari, Samad Baig, Atif Amin Bantie, Abere Tilahun Barrow, Amadou Baskaran, Pritish Basu, Sanjay Batiha, Abdul-Monim Mohammad Baune, Bernhard T. Berezvai, Zombor Bhardwaj, Nikha Bhardwaj, Pankaj Bhaskar, Sonu Boachie, Micheal Kofi Bodolica, Virginia Botelho, João Silva Botelho Braithwaite, Dejana Breitborde, Nicholas J.K. Busse, Reinhard Cahuana-Hurtado, Lucero Catalá-López, Ferrán Chansa, Collins Charan, Jaykaran Chattu, Vijay Kumar Chen, Simiao Chukwu, Isaac Sunday Dadras, Omid Dandona, Lalit Dandona, Rakhi Dargahi, Abdollah Debela, Sisay Abebe Denova-Gutiérrez, Edgar Desye, Belay Dharmaratne, Samath Dhamminda Diao, Nancy Doan, Linh Phuong Dodangeh, Milad dos Santos, Wendel Mombaque Doshmangir, Leila Dube, John Eini, Ebrahim El Sayed Zaki, Maysaa El Tantawi, Maha Enyew, Daniel Berhanie Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Applied Mathematics University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Nuffield Department of Medicine University of Oxford Oxford United Kingdom Department of Juridical and Economic Studies La Sapienza University Rome Italy Antai College of Economics Shanghai Jiao Tong University Shanghai China Non-communicable Diseases Research Center Tehran University of Medical Sciences Tehran Iran Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Center Tehran University of Medical Sciences Tehran Iran Children’s Medical Center Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Tehran Heart Center Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Tehran University of Medical Sciences Tehran Iran National Institute for Health Research Tehran University of Medical Sciences Tehran Iran Department of Pharmacology Tehran University of Medical Sciences Tehran Iran Department of Cardiology Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Center Tehran University of Medical Sciences Tehran Iran Digestive Diseases Research Institute Tehran University of Medical Sciences Tehran Iran Department of Neurology Tehran University of Medical Sciences Tehran Iran Social Determinants of Health Research Center Shahid Beheshti University of Medical Sciences Tehran Iran Department of Epidemiology Shahid Beheshti University of Medical Sciences Tehran Iran Department of Health Economics and Statistics Shahid Beheshti University of Medical Sciences Tehran Iran Department of Neurosurgery Shahid Beheshti University of Medical Sciences Tehran Iran Ophthalmic R

Background: The COVID-19 pandemic highlighted gaps in health surveillance systems, disease prevention, and treatment globally. Among the many factors that might have led to these gaps is the issue of the financing of national health systems, especially in low-income and middle-income countries (LMICs), as well as a robust global system for pandemic preparedness. We aimed to provide a comparative assessment of global health spending at the onset of the pandemic;characterise the amount of development assistance for pandemic preparedness and response disbursed in the first 2 years of the COVID-19 pandemic;and examine expectations for future health spending and put into context the expected need for investment in pandemic preparedness. Methods: In this analysis of global health spending between 1990 and 2021, and prediction from 2021 to 2026, we estimated four sources of health spending: development assistance for health (DAH), government spending, out-of-pocket spending, and prepaid private spending across 204 countries and territories. We used the Organisation for Economic Co-operation and Development (OECD)'s Creditor Reporting system (CRS) and the WHO Global Health Expenditure Database (GHED) to estimate spending. We estimated development assistance for general health, COVID-19 response, and pandemic preparedness and response using a keyword search. Health spending estimates were combined with estimates of resources needed for pandemic prevention and preparedness to analyse future health spending patterns, relative to need. Findings: In 2019, at the onset of the COVID-19 pandemic, US$9·2 trillion (95% uncertainty interval [UI] 9·1–9·3) was spent on health worldwide. We found great disparities in the amount of resources devoted to health, with high-income countries spending $7·3 trillion (95% UI 7·2–7·4) in 2019;293·7 times the $24·8 billion (95% UI 24·3–25·3) spent by low-income countries in 2019. That same year, $43·1 billion in development assistance was provided

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Erratum to: Search for dark matter produced in association with a leptonically decaying Z boson in proton–proton collisions at s = 13 Te

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The European Physical Journal C 2021年第4期81卷 1-16页

作者： A. M. Sirunyan A. Tumasyan W. Adam T. Bergauer M. Dragicevic J. Erö A. Escalante Del Valle R. Frühwirth M. Jeitler N. Krammer L. Lechner D. Liko T. Madlener I. Mikulec F. M. Pitters N. Rad J. Schieck R. Schöfbeck M. Spanring S. Templ W. Waltenberger C.-E. Wulz M. Zarucki V. Chekhovsky A. Litomin V. Makarenko J. Suarez Gonzalez M. R. Darwish E. A. De Wolf D. Di Croce X. Janssen T. Kello A. Lelek M. Pieters H. Rejeb Sfar H. Van Haevermaet P. Van Mechelen S. Van Putte N. Van Remortel F. Blekman E. S. Bols S. S. Chhibra J. D’Hondt J. De Clercq D. Lontkovskyi S. Lowette I. Marchesini S. Moortgat A. Morton Q. Python S. Tavernier W. Van Doninck P. Van Mulders D. Beghin B. Bilin B. Clerbaux G. De Lentdecker B. Dorney L. Favart A. Grebenyuk A. K. Kalsi I. Makarenko L. Moureaux L. Pétré A. Popov N. Postiau E. Starling L. Thomas C. Vander Velde P. Vanlaer D. Vannerom L. Wezenbeek T. Cornelis D. Dobur M. Gruchala I. Khvastunov M. Niedziela C. Roskas K. Skovpen M. Tytgat W. Verbeke B. Vermassen M. Vit G. Bruno F. Bury C. Caputo P. David C. Delaere M. Delcourt I. S. Donertas A. Giammanco V. Lemaitre K. Mondal J. Prisciandaro A. Taliercio M. Teklishyn P. Vischia S. Wuyckens J. Zobec G. A. Alves C. Hensel A. Moraes W. L. Aldá Júnior E. Belchior Batista Das Chagas H. BRANDAO MALBOUISSON W. Carvalho J. Chinellato E. Coelho E. M. Da Costa G. G. Da Silveira D. De Jesus Damiao S. Fonseca De Souza J. Martins D. Matos Figueiredo M. Medina Jaime C. Mora Herrera L. Mundim H. Nogima P. Rebello Teles L. J. Sanchez Rosas A. Santoro S. M. Silva Do Amaral A. Sznajder M. Thiel F. Torres Da Silva De Araujo A. Vilela Pereira C. A. Bernardes L. Calligaris T. R. Fernandez Perez Tomei E. M. Gregores D. S. Lemos P. G. Mercadante S. F. Novaes Sandra S. Padula A. Aleksandrov G. Antchev I. Atanasov R. Hadjiiska P. Iaydjiev M. Misheva M. Rodozov M. Shopova G. Sultanov M. Bonchev A. Dimitrov T. Ivanov L. Litov B. Pavlov P. Petkov A. Petrov W. Fang Q. Guo H. Wang L. Yuan M. Ahmad Z. Hu Y. Wang E. Chapon G. M. Chen H. S. Chen M. Chen A. Kapoor D. Leggat H. Yerevan Physics Institute Yerevan Armenia Institut für Hochenergiephysik Vienna Austria Vienna University of Technology Vienna Austria Institute for Nuclear Problems Minsk Belarus Universiteit Antwerpen Antwerpen Belgium Department of Basic and Applied Sciences Faculty of Engineering Arab Academy for Science Technology and Maritime Transport Alexandria Egypt Université Libre de Bruxelles Bruxelles Belgium Vrije Universiteit Brussel Brussel Belgium Ghent University Ghent Belgium IRFU CEA Université Paris-Saclay Gif-sur-Yvette France Université Catholique de Louvain Louvain-la-Neuve Belgium Centro Brasileiro de Pesquisas Fisicas Rio de Janeiro Brazil Universidade do Estado do Rio de Janeiro Rio de Janeiro Brazil Universidade Estadual de Campinas Campinas Brazil Federal University of Rio Grande do Sul Porto Alegre Brazil UFMS Nova Andradina Brazil Universidade Federal de Pelotas Pelotas Brazil Universidade Estadual Paulista Universidade Federal do ABC São Paulo Brazil Institute for Nuclear Research and Nuclear Energy Bulgarian Academy of Sciences Sofia Bulgaria University of Sofia Sofia Bulgaria Beihang University Beijing China Department of Physics Tsinghua University Beijing China Institute of High Energy Physics Beijing China University of Chinese Academy of Sciences Beijing China State Key Laboratory of Nuclear Physics and Technology Peking University Beijing China Sun Yat-Sen University Guangzhou China Institute of Modern Physics and Key Laboratory of Nuclear Physics and Ion-beam Application (MOE) - Fudan University Shanghai China Zhejiang University Hangzhou China Universidad de Los Andes Bogota Colombia Universidad de Antioquia Medellin Colombia University of Split Faculty of Electrical Engineering Mechanical Engineering and Naval Architecture Split Croatia University of Split Faculty of Science Split Croatia Institute Rudjer Boskovic Zagreb Croatia Institute for Theoretical and Experimental Physics named by A.I. Alikhanov of NRC ‘K

A Correction to this paper has been published: https://***/10.1140/epjc/s10052-020-08739-5

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Towards an Algorithm and Communication Cost Model for the Parallel Particle Swarm Optimization

Towards an Algorithm and Communication Cost Model for the Pa...

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ARCS 2016;29th International Conference on architecture of Computing systems

作者： Romeo Shuka Sebastian Niemann Juergen Brehm Christian Mueller-Schloer Institute of Systems Engineering System and Computer Architecture Leibniz Universitat Hannover

The adaptation of sequential algorithms for High Performance Computing (HPC) systems is determined by a tradeoff between algorithmic effectiveness (software) and communication frequency (hardware) of the parallel implementation (efficiency). To get a better understanding of the correlation, we define simple models for both, software and hardware, in order to dynamically find the best mapping parameters for the execution of the algorithm on the parallel system. For the evaluation of our method we look at population-based algorithms like the Particle Swarm Optimization Algorithm (PSO) for the solution of optimization problems. Different goals like best quality of the solution of the optimization problem for a given execution time or best execution time to find the optimum are defined by the user. Our method enables us to find the best parameters for the mapping which then results in an efficient and effective parallel implementation to achieve the user-defined goals on a High Performance Computing Cluster (HPCC).

关键词： High Performance Computing Optimization algorithms Particle Swarm Optimization Particle swarm optimization High Performance Computing Optimization algorithms algorithms execution time parallel system computer hardware Parallel Lines

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The Liver Tumor Segmentation Benchmark (LiTS)

arXiv

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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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Case study: Approximations of the bessel function

arXiv

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arXiv 2017年

作者： Karachalios, D.S. Gosea, I.V. Zhang, Q. Antoulas, A.C. Data-Driven System Reduction and Identification Group Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany Department of Electrical and Computer Engineering Rice University Houston United States

The purpose of this note is to compare various approximation methods as applied to the inverse of the Bessel function of the first kind J01(s), in a given domain of the complex plane.30E10, 03C40, 65E99 Copyright ... 详细信息

关键词： Bessel functions

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Training of transport specialists and self-regulation of teachers and managers of educational institutions as human capital development strategy

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IOP Conference Series: Materials Science and engineering 2020年第1期918卷

作者： E N Kamenskaya R T Kokoeva M V Panichkina I V Burova G K Kassymova M R Arpentieva Institute of Management in the Economic Environmental and Social Systems of the Southern Federal University Rostov Region Taganrog Russian Federation Department of Psychology Psychological and Pedagogical Faculty K.L. Khetagurov North-Ossetian State University Vladikavkaz Southern Federal University Taganrog Rostov-on-Don Russian Federation Department of Higher Mathematics and Computer Science Academy of civil engineering and Architecture V.I. Vernadskiy Crimean Federal University Simferopol Republic of Crimea Russian Federation Department of intellectual properties and international cooperation in the Institute of Metallurgy and Ore Beneficiation at Satbayev University Department of Pedagogy and Psychology at Abay Kazakh National Pedagogical University Almaty Republic of Kazakhstan Graduate school at Yogyakarta State University Yogyakarta Indonesia Department at the development and education psychology Tsiolkovskiy Kaluga state University Kaluga Russian Federation

Improving the quality of human capital in transport is closely related to the development of the ability of transport specialists to self-regulation. The training of modern, qualified transport specialists (as human capital development strategy) requires no less highly qualified teachers and managers, capable of not only managing others, but also themselves. In modern socio-cultural space, researchers pay special attention to the preservation and development of man as the highest value, the recognition and upholding of him as the highest value on earth. Such an understanding assumes the professionalism of consultative interaction with the client as a person, partner and professional, based on a detailed analysis of the characteristics and properties, processes and results of human activities. Appeal to followers in understanding the human mental life is associated with well-known methods for diagnosing and transforming the most complex internal world of a person, as well as the features, processes and results of the interaction of the internal and external worlds surrounding a person. Psychological comprehension of a person, penetration into the matrix structures of his personal, interpersonal and professional formation and development is sometimes serious difficulties, so our appeal to the psychodynamic and behavioural models of self-regulation, as well as in social and individual psychology and their methods, is dictated by these ideas. The appeal to classical conceptual constructs, in particular, modern and traditional domestic and foreign psychology, allows us to comprehend and practically develop methods and methods of immersion in the mental world of a person, his research, as well as subsequent transformation and development.

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Author Correction: Federated learning enables big data for rare cancer boundary detection

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Nature communications 2023年第1期14卷 436页

作者： Sarthak Pati Ujjwal Baid Brandon Edwards Micah Sheller Shih-Han Wang G Anthony Reina Patrick Foley Alexey Gruzdev Deepthi Karkada Christos Davatzikos Chiharu Sako Satyam Ghodasara Michel Bilello Suyash Mohan Philipp Vollmuth Gianluca Brugnara Chandrakanth J Preetha Felix Sahm Klaus Maier-Hein Maximilian Zenk Martin Bendszus Wolfgang Wick Evan Calabrese Jeffrey Rudie Javier Villanueva-Meyer Soonmee Cha Madhura Ingalhalikar Manali Jadhav Umang Pandey Jitender Saini John Garrett Matthew Larson Robert Jeraj Stuart Currie Russell Frood Kavi Fatania Raymond Y Huang Ken Chang Carmen Balaña Jaume Capellades Josep Puig Johannes Trenkler Josef Pichler Georg Necker Andreas Haunschmidt Stephan Meckel Gaurav Shukla Spencer Liem Gregory S Alexander Joseph Lombardo Joshua D Palmer Adam E Flanders Adam P Dicker Haris I Sair Craig K Jones Archana Venkataraman Meirui Jiang Tiffany Y So Cheng Chen Pheng Ann Heng Qi Dou Michal Kozubek Filip Lux Jan Michálek Petr Matula Miloš Keřkovský Tereza Kopřivová Marek Dostál Václav Vybíhal Michael A Vogelbaum J Ross Mitchell Joaquim Farinhas Joseph A Maldjian Chandan Ganesh Bangalore Yogananda Marco C Pinho Divya Reddy James Holcomb Benjamin C Wagner Benjamin M Ellingson Timothy F Cloughesy Catalina Raymond Talia Oughourlian Akifumi Hagiwara Chencai Wang Minh-Son To Sargam Bhardwaj Chee Chong Marc Agzarian Alexandre Xavier Falcão Samuel B Martins Bernardo C A Teixeira Flávia Sprenger David Menotti Diego R Lucio Pamela LaMontagne Daniel Marcus Benedikt Wiestler Florian Kofler Ivan Ezhov Marie Metz Rajan Jain Matthew Lee Yvonne W Lui Richard McKinley Johannes Slotboom Piotr Radojewski Raphael Meier Roland Wiest Derrick Murcia Eric Fu Rourke Haas John Thompson David Ryan Ormond Chaitra Badve Andrew E Sloan Vachan Vadmal Kristin Waite Rivka R Colen Linmin Pei Murat Ak Ashok Srinivasan J Rajiv Bapuraj Arvind Rao Nicholas Wang Ota Yoshiaki Toshio Moritani Sevcan Turk Joonsang Lee Snehal Prabhudesai Fanny Morón Jacob Mandel Konstantinos Kamnitsas Ben Glocker Luke V M Dixon Matthew Williams Peter Zamp Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA. Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Department of Informatics Technical University of Munich Munich Bavaria Germany. Intel Corporation Santa Clara CA USA. Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany. Clinical Cooperation Unit Neuropathology German Cancer Consortium (DKTK) within the German Cancer Research Center (DKFZ) Heidelberg Germany. Department of Neuropathology Heidelberg University Hospital Heidelberg Germany. Division of Medical Image Computing German Cancer Research Center Heidelberg Germany. Pattern Analysis and Learning Group Department of Radiation Oncology Heidelberg University Hospital Heidelberg Germany. Neurology Clinic Heidelberg University Hospital Heidelberg Germany. Department of Radiology & Biomedical Imaging University of California San Francisco San Francisco CA USA. Symbiosis Center for Medical Image Analysis Symbiosis International University Pune Maharashtra India. Department of Neuroimaging and Interventional Radiology National Institute of Mental Health and Neurosciences Bangalore Karnataka India. Department of Radiology School of Medicine and Public Health University of Wisconsin Madison WI USA. Department of Medical Physics School of Medicine and Public Health University of Wisconsin Madison WI USA. Leeds Teaching Hospitals Trust Department of Radiology Leeds UK. Department of Radiology Brigham and Women's Hospital Harvard Medical School Boston MA USA. Athinoula A. Martinos Center for Biomedical Imaging Massachusetts General Hospital Charlestown MA USA. Catalan Institute of Oncology Badalona Spain. Consorci MAR Parc de Salut de Barcelona Catalonia Spain. Department of Radiology (IDI

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