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arXiv 2018年

作者： Veta, Mitko Heng, Yujing J. Stathonikos, Nikolas Bejnordi, Babak Ehteshami Beca, Francisco Wollmann, Thomas Rohr, Karl Shah, Manan A. Wang, Dayong Rousson, Mikael Hedlund, Martin Tellez, David Ciompi, Francesco Zerhouni, Erwan Lanyi, David Viana, Matheus Kovalev, Vassili Liauchuk, Vitali Phoulady, Hady Ahmady Qaiser, Talha Graham, Simon Rajpoot, Nasir Sjöblom, Erik Molin, Jesper Paeng, Kyunghyun Hwang, Sangheum Park, Sunggyun Jia, Zhipeng Chang, Eric I-Chao Xu, Yan Beck, Andrew H. Van Diest, Paul J. Pluim, Josien P.W. Medical Image Analysis Group Eindhoven University of Technology Eindhoven Netherlands Department of Pathology Beth Israel Deaconess Medical Center Harvard Medical School BostonMA United States Department of Pathology University Medical Center Utrecht Utrecht Netherlands Diagnostic Image Analysis Group Radboud University Medical Center Nijmegen Netherlands Department of Pathology Stanford University School of Medicine Biomedical Computer Vision Group University of Heidelberg BIOQUANT IPMB DKFZ Heidelberg Germany Harker School San Jose United States ContextVision AB Linköping Sweden Foundations of Cognitive Computing IBM Research Zürich Rüschlikon Switzerland Visual Analytics and Insights IBM Research Brazil Saõ Paulo Brazil Biomedical Image Analysis Department United Institute of Informatics Minsk Belarus Department of Computer Science and Engineering University of South Florida TampaFL United States Department of Computer Science University of Warwick Warwick United Kingdom Research Sectra Linköping Sweden Lunit Inc. Seoul Korea Republic of Institute for Interdisciplinary Information Sciences Tsinghua University Beijing China Microsoft Research Beijing China Biology and Medicine Engineering Beihang University Beijing China IBM Research Brazil

Tumor proliferation is an important biomarker indicative of the prognosis of breast cancer patients. Assessment of tumor proliferation in a clinical setting is a highly subjective and labor-intensive task. Previous efforts to automate tumor proliferation assessment by image analysis only focused on mitosis detection in predefined tumor regions. However, in a realworld scenario, automatic mitosis detection should be performed in whole-slide images (WSIs) and an automatic method should be able to produce a tumor proliferation score given a WSI as input. To address this, we organized the TUmor Proliferation Assessment Challenge 2016 (TUPAC16) on prediction of tumor proliferation scores from WSIs. The challenge dataset consisted of 500 training and 321 testing breast cancer histopathology WSIs. In order to ensure fair and independent evaluation, only the ground truth for the training dataset was provided to the challenge participants. The first task of the challenge was to predict mitotic scores, i.e., to reproduce the manual method of assessing tumor proliferation by a pathologist. The second task was to predict the gene expression based PAM50 proliferation scores from the WSI. The best performing automatic method for the first task achieved a quadratic-weighted Cohen's kappa score of κ = 0.567, 95% CI [0.464, 0.671] between the predicted scores and the ground truth. For the second task, the predictions of the top method had a Spearman's correlation coefficient of r = 0.617, 95% CI [0.581 0.651] with the ground truth. This was the first comparison study that investigated tumor proliferation assessment from WSIs. The achieved results are promising given the difficulty of the tasks and weakly-labeled nature of the ground truth. However, further research is needed to improve the practical utility of image analysis methods for this task. Copyright © 2018, The Authors. All rights reserved.

关键词： Diseases

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A statistical approach to increase classification accuracy in supervised learning algorithms

arXiv

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arXiv 2017年

作者： Valencia-Zapata, Gustavo A. Mejia, Daniel Klimeck, Gerhard Zentner, Michael G. Ersoy, Okan School of Electrical and Computer Engineering Purdue University United States Network for Computational Nanotechnology Cyber Node Purdue University United States HUBzero Research Group Information Technology at Purdue Electrical and Computer Engineering Purdue University Bogazici University Istanbul Turkey

Probabilistic mixture models have been widely used for different machine learning and pattern recognition tasks such as clustering, dimensionality reduction, and classification. In this paper, we focus on trying to solve the most common challenges related to supervised learning algorithms by using mixture probability distribution functions. With this modeling strategy, we identify sub-labels and generate synthetic data in order to reach better classification accuracy. It means we focus on increasing the training data synthetically to increase the classification accuracy. Copyright © 2017, The Authors. All rights reserved.

关键词： Supervised learning

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Multiharmonic Correlations of Different Flow Amplitudes in Pb-Pb Collisions at sNN=2.76 TeV

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Physical Review Letters 2021年第9期127卷 092302-092302页

作者： S. Acharya D. Adamová A. Adler J. Adolfsson G. Aglieri Rinella M. Agnello N. Agrawal Z. Ahammed S. Ahmad S. U. Ahn Z. Akbar A. Akindinov M. Al-Turany D. S. D. Albuquerque D. Aleksandrov B. Alessandro H. M. Alfanda R. Alfaro Molina B. Ali Y. Ali A. Alici N. Alizadehvandchali A. Alkin J. Alme T. Alt L. Altenkamper I. Altsybeev M. N. Anaam C. Andrei D. Andreou A. Andronic V. Anguelov T. Antičić F. Antinori P. Antonioli C. Anuj N. Apadula L. Aphecetche H. Appelshäuser S. Arcelli R. Arnaldi M. Arratia I. C. Arsene M. Arslandok A. Augustinus R. Averbeck S. Aziz M. D. Azmi A. Badalà Y. W. Baek X. Bai R. Bailhache R. Bala A. Balbino A. Baldisseri M. Ball D. Banerjee R. Barbera L. Barioglio M. Barlou G. G. Barnaföldi L. S. Barnby V. Barret C. Bartels K. Barth E. Bartsch F. Baruffaldi N. Bastid S. Basu G. Batigne B. Batyunya D. Bauri J. L. Bazo Alba I. G. Bearden C. Beattie I. Belikov A. D. C. Bell Hechavarria F. Bellini R. Bellwied S. Belokurova V. Belyaev G. Bencedi S. Beole A. Bercuci Y. Berdnikov A. Berdnikova D. Berenyi L. Bergmann M. G. Besoiu L. Betev P. P. Bhaduri A. Bhasin I. R. Bhat M. A. Bhat B. Bhattacharjee P. Bhattacharya A. Bianchi L. Bianchi N. Bianchi J. Bielčík J. Bielčíková A. Bilandzic G. Biro S. Biswas J. T. Blair D. Blau M. B. Blidaru C. Blume G. Boca F. Bock A. Bogdanov S. Boi J. Bok L. Boldizsár A. Bolozdynya M. Bombara P. M. Bond G. Bonomi H. Borel A. Borissov H. Bossi E. Botta L. Bratrud P. Braun-Munzinger M. Bregant M. Broz G. E. Bruno M. D. Buckland D. Budnikov H. Buesching S. Bufalino O. Bugnon P. Buhler P. Buncic Z. Buthelezi J. B. Butt S. A. Bysiak D. Caffarri A. Caliva E. Calvo Villar J. M. M. Camacho R. S. Camacho P. Camerini F. D. M. Canedo A. A. Capon F. Carnesecchi R. Caron J. Castillo Castellanos E. A. R. Casula F. Catalano C. Ceballos Sanchez P. Chakraborty S. Chandra W. Chang S. Chapeland M. Chartier S. Chattopadhyay A. Chauvin T. G. Chavez C. Cheshkov B. Cheynis V. Chibante Barroso D. D. Chinellato S. Cho P. Chochula P. Christakoglou C. H. Christensen P. Christiansen T. Chujo C. Cica Variable Energy Cyclotron Centre Homi Bhabha National Institute Kolkata India Nuclear Physics Institute of the Czech Academy of Sciences Řež u Prahy Czech Republic Johann-Wolfgang-Goethe Universität Frankfurt Institut für Informatik Fachbereich Informatik und Mathematik Frankfurt Germany Lund University Department of Physics Division of Particle Physics Lund Sweden European Organization for Nuclear Research (CERN) Geneva Switzerland Dipartimento DISAT del Politecnico and Sezione INFN Turin Italy INFN Sezione di Bologna Bologna Italy Department of Physics Aligarh Muslim University Aligarh India Korea Institute of Science and Technology Information Daejeon Republic of Korea Indonesian Institute of Sciences Jakarta Indonesia NRC « Kurchatov»what Institute—ITEP Moscow Russia Research Division and ExtreMe Matter Institute EMMI GSI Helmholtzzentrum für Schwerionenforschung GmbH Darmstadt Germany Universidade Estadual de Campinas (UNICAMP) Campinas Brazil National Research Centre Kurchatov Institute Moscow Russia INFN Sezione di Torino Turin Italy Central China Normal University Wuhan China Instituto de Física Universidad Nacional Autónoma de México Mexico City Mexico COMSATS University Islamabad Islamabad Pakistan Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN Bologna Italy University of Houston Houston Texas USA Department of Physics and Technology University of Bergen Bergen Norway Institut für Kernphysik Johann Wolfgang Goethe-Universität Frankfurt Frankfurt Germany St. Petersburg State University St. Petersburg Russia Horia Hulubei National Institute of Physics and Nuclear Engineering Bucharest Romania Nikhef National institute for subatomic physics Amsterdam Netherlands Westfälische Wilhelms-Universität Münster Institut für Kernphysik Münster Germany Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Rudjer Bošković Institute Zagreb Croatia INFN Sezione di Padova Padova Italy Lawrence Berkel

The event-by-event correlations between three flow amplitudes are measured for the first time in Pb-Pb collisions, using higher-order symmetric cumulants. We find that different three-harmonic correlations develop during the collective evolution of the medium when compared to correlations that exist in the initial state. These new results cannot be interpreted in terms of previous lower-order flow measurements since contributions from two-harmonic correlations are explicitly removed in the new observables. A comparison to Monte Carlo simulations provides new and independent constraints for the initial conditions and system properties of nuclear matter created in heavy-ion collisions.

关键词： Nuclear reactions

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Bi-target tracking based on vortex wave with orbital angular momentum

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Progress In Electromagnetics research C 2017年 74卷 123-129页

作者： Tang, Bo Bai, Jian Guo, Kunyi School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China Science and Technology on Millimeter-wave Laboratory Second Research Institute of the China Aerospace Science and Industry Group Beijing100039 China Center for Electromagnetic Simulation School of Information and Electronics Beijing Institute of Technology Beijing100081 China

This paper studies the application of vortex wave with orbital angular momentum (OAM) in the radar. The vortex waves can have eigenstates or modes with different integer topological charges, which are orthogonal to each other. The eigenstates with topological charges of 0, −1 and 1 were utilized in this paper. The radar transmitted the pulse with topological charge of 0 and received echoes with topological charges of 0, −1 and 1. The receiver can process the signals received by these orthogonal modes to obtain the azimuth and elevation angles of the two targets in a same range gate. Compared with the traditional mono-pulse radar only with sum beam and difference beam, this vortex-wave-based radar can track two targets in principle. This is meaningful for the application of the vortex wave. © 2017, Electromagnetics Academy. All rights reserved.

关键词： Vortex flow

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Measurement of the Cross Sections of Ξc0 and Ξc+ Baryons and of the Branching-Fraction Ratio BR(Ξc0→Ξ−e+νe)/BR(Ξc0→Ξ−π+) in pp Collisions at s=13 TeV

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Physical Review Letters 2021年第27期127卷 272001-272001页

作者： S. Acharya D. Adamová A. Adler J. Adolfsson G. Aglieri Rinella M. Agnello N. Agrawal Z. Ahammed S. Ahmad S. U. Ahn I. Ahuja Z. Akbar A. Akindinov M. Al-Turany S. N. Alam D. Aleksandrov B. Alessandro H. M. Alfanda R. Alfaro Molina B. Ali Y. Ali A. Alici N. Alizadehvandchali A. Alkin J. Alme T. Alt L. Altenkamper I. Altsybeev M. N. Anaam C. Andrei D. Andreou A. Andronic M. Angeletti V. Anguelov F. Antinori P. Antonioli C. Anuj N. Apadula L. Aphecetche H. Appelshäuser S. Arcelli R. Arnaldi I. C. Arsene M. Arslandok A. Augustinus R. Averbeck S. Aziz M. D. Azmi A. Badalà Y. W. Baek X. Bai R. Bailhache Y. Bailung R. Bala A. Balbino A. Baldisseri B. Balis M. Ball D. Banerjee R. Barbera L. Barioglio M. Barlou G. G. Barnaföldi L. S. Barnby V. Barret C. Bartels K. Barth E. Bartsch F. Baruffaldi N. Bastid S. Basu G. Batigne B. Batyunya D. Bauri J. L. Bazo Alba I. G. Bearden C. Beattie I. Belikov A. D. C. Bell Hechavarria F. Bellini R. Bellwied S. Belokurova V. Belyaev G. Bencedi S. Beole A. Bercuci Y. Berdnikov A. Berdnikova D. Berenyi L. Bergmann M. G. Besoiu L. Betev P. P. Bhaduri A. Bhasin I. R. Bhat M. A. Bhat B. Bhattacharjee P. Bhattacharya L. Bianchi N. Bianchi J. Bielčík J. Bielčíková J. Biernat A. Bilandzic G. Biro S. Biswas J. T. Blair D. Blau M. B. Blidaru C. Blume G. Boca F. Bock A. Bogdanov S. Boi J. Bok L. Boldizsár A. Bolozdynya M. Bombara P. M. Bond G. Bonomi H. Borel A. Borissov H. Bossi E. Botta L. Bratrud P. Braun-Munzinger M. Bregant M. Broz G. E. Bruno M. D. Buckland D. Budnikov H. Buesching S. Bufalino O. Bugnon P. Buhler Z. Buthelezi J. B. Butt S. A. Bysiak D. Caffarri M. Cai H. Caines A. Caliva E. Calvo Villar J. M. M. Camacho R. S. Camacho P. Camerini F. D. M. Canedo F. Carnesecchi R. Caron J. Castillo Castellanos E. A. R. Casula F. Catalano C. Ceballos Sanchez P. Chakraborty S. Chandra S. Chapeland M. Chartier S. Chattopadhyay A. Chauvin T. G. Chavez C. Cheshkov B. Cheynis V. Chibante Barroso D. D. Chinellato S. Cho P. Chochula P. Christakoglou C. H. Christensen P. Christiansen T. Chujo C. Cicalo L Variable Energy Cyclotron Centre Homi Bhabha National Institute Kolkata India Nuclear Physics Institute of the Czech Academy of Sciences Řež u Prahy Czech Republic Johann-Wolfgang-Goethe Universität Frankfurt Institut für Informatik Fachbereich Informatik und Mathematik Frankfurt Germany Lund University Department of Physics Division of Particle Physics Lund Sweden European Organization for Nuclear Research (CERN) Geneva Switzerland Dipartimento DISAT del Politecnico and Sezione INFN Turin Italy INFN Sezione di Bologna Bologna Italy Department of Physics Aligarh Muslim University Aligarh India Korea Institute of Science and Technology Information Daejeon Republic of Korea Faculty of Science P.J. Šafárik University Košice Slovakia Indonesian Institute of Sciences Jakarta Indonesia NRC «Kurchatov» Institute—ITEP Moscow Russia Research Division and ExtreMe Matter Institute EMMI GSI Helmholtzzentrum für Schwerionenforschung GmbH Darmstadt Germany Fudan University Shanghai China National Research Centre Kurchatov Institute Moscow Russia INFN Sezione di Torino Turin Italy Central China Normal University Wuhan China Instituto de Física Universidad Nacional Autónoma de México Mexico City Mexico COMSATS University Islamabad Islamabad Pakistan Dipartimento di Fisica e Astronomia dell’Università and Sezione INFN Bologna Italy University of Houston Houston Texas USA Department of Physics and Technology University of Bergen Bergen Norway Institut für Kernphysik Johann Wolfgang Goethe-Universität Frankfurt Frankfurt Germany St. Petersburg State University St. Petersburg Russia Horia Hulubei National Institute of Physics and Nuclear Engineering Bucharest Romania Nikhef National institute for subatomic physics Amsterdam Netherlands Westfälische Wilhelms-Universität Münster Institut für Kernphysik Münster Germany Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany INFN Sezione di Padova Padova Italy Lawrence Berkeley National La

The pT-differential cross sections of prompt charm-strange baryons Ξc0 and Ξc+ were measured at midrapidity (|y|<0.5) in proton-proton (pp) collisions at a center-of-mass energy s=13 TeV with the ALICE detector at the LHC. The Ξc0 baryon was reconstructed via both the semileptonic decay (Ξ−e+νe) and the hadronic decay (Ξ−π+) channels. The Ξc+ baryon was reconstructed via the hadronic decay (Ξ−π+π+) channel. The branching-fraction ratio BR(Ξc0→Ξ−e+νe)/BR(Ξc0→Ξ−π+)=1.38±0.14(stat)±0.22(syst) was measured with a total uncertainty reduced by a factor of about 3 with respect to the current world average reported by the Particle Data group. The transverse momentum (pT) dependence of the Ξc0- and Ξc+-baryon production relative to the D0 meson and to the Σc0,+,++- and Λc+-baryon production are reported. The baryon-to-meson ratio increases toward low pT up to a value of approximately 0.3. The measurements are compared with various models that take different hadronization mechanisms into consideration. The results provide stringent constraints to these theoretical calculations and additional evidence that different processes are involved in charm hadronization in electron-positron (e+e−) and hadronic collisions.

关键词： Hadron-hadron interactions

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BioTIME 2.0: Expanding and Improving a Database of Biodiversity Time Series

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Global Ecology and Biogeography 2025年第5期34卷

作者： Maria Dornelas Laura H. Antão Amanda E. Bates Viviana Brambilla Jonathan M. Chase Cher F. Y. Chow Ada Fontrodona-Eslava Anne E. Magurran Inês S. Martins Faye Moyes Alban Sagouis Samuel Adu-Acheampong Daniel Acquah-Lamptey Dušan Adam Penelope A. Ajani Aitor Albaina Pablo Almaraz Jeongseop An Roger Sigismund Anderson Madelaine Jean Robertson Anderson Alexsander Z. Antunes Ivan Arismendi Linda Armbrecht Pedro Aros-Mardones Sreejith Kalpuzha Ashtamoorthy Narayanan Ayyappan Gal Badihi Joseph J. Bailey Andrew H. Baird Mark Edward Baird Sreekumar Vadakkethil Balakrishnan José António L. Barão-Nóbrega Adi Barash Miguel Barbosa Jos Barlow Claus Bässler Matthieu Beaumont Natalie Beenaerts Tiago Octavio Begot Wallace Beiroz Ricardo Beldade David M. Bell Alecia Bellgrove Jonathan Belmaker Lisandro Benedetti-Cecchi Cassandra E. Benkwitt Pamela Medina-van Berkum Brandon T. Bestelmeyer Matthew G. Betts Maxwell Kelvin Billah Anne D. Bjorkman Magdalena Błażewicz Christopher P. Bloch Shane A. Blowes Antonio Bode Juliano A. Bogoni Thomas Bolger Timothy C. Bonebrake Erik Bonsdorff Roberta Bottarin Luke N. Brokensha Rob W. Brooker Andrew J. Brooks Helge Bruelheide Thiago Almeida Bueno Claire Laguionie Mariana Lopes Campagnoli James Cant Erica Pellegrini Caramaschi Alexandre Caron Tadhg Carroll Tancredi Caruso Juan Carvajal-Quintero Giuseppe Castaldelli Edward Castañeda-Moya Pedro V. Castilho Sonia Zanini Cechin Shahar Chaikin Uchangi Manjunatha Chandrashekara Tory J. Chase Chaolun Allen Chen Jorge José Cherem Sei-Woong Choi Erica M. Christensen Alexander V. Christianini Jackson Wing Four Chu Peter Coad Carl Van Colen Lise Comte Elisabeth J. Cooper J. Hans C. Cornelissen Eddy Cosson Unai Cotano Luc Crevecoeur Shannan Kyle Crow Graeme S. Cumming Vanessa S. Daga Gabriella Damasceno Gergana N. Daskalova Claire H. Davies Robert A. Davis Frank P. Day Sussy De-La-Zerda Amy Elizabeth Deacon Indradatta de Castro-Arrazola Steven Degraer Kharran Deonarinesingh Juan C. Diaz-Ricaurte Christopher R. Dickman Tara Dirilgen Ciaran John Dolan J. Emmet Centre for Biological Diversity School of Biology University of St Andrews Fife UK MARE—Centro de Ciências do Mar e do Ambiente Faculdade de Ciências Universidade de Lisboa Lisboa Portugal Research Centre for Ecological Change Organismal and Evolutionary Biology Research Programme Faculty of Biological and Environmental Sciences University of Helsinki Helsinki Finland Department of Biology University of Victoria Victoria British Columbia Canada German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig Leipzig Germany Department of Computer Science Martin Luther University Halle-Wittenberg Halle (Saale) Germany Leverhulme Centre for Anthropocene Biodiversity Department of Biology University of York York UK Department of Animal Biology and Conservation Science University of Ghana Accra Ghana Philipps Universität Marburg Marburg Germany Department of Forest Ecology Silva Tarouca Research Institute Brno Czech Republic School of Life Sciences University of Technology Sydney Sydney New South Wales Australia Zoology and Animal Cell Biology Department University of the Basque Country (UPV/EHU) Leioa Spain Grupo de Oceanografía de Ecosistemas Instituto de Ciencias Marinas de Andalucía CSIC Campus Universitario de Puerto Real Puerto Real Spain National Institute of Ecology Seocheon Republic of Korea African Regional Postgraduate Programme in Insect Science University of Ghana Accra Ghana Département de Biologie Université de Sherbrooke Sherbrooke Quebec Canada Núcleo de Conservação da Biodiversidade Instituto de Pesquisas Ambientais Secretaria de Meio Ambiente Infraestrutura e Logística do Estado de São Paulo São Paulo Brazil Department of Fisheries Wildlife and Conservation Sciences Oregon State University Corvallis Oregon USA Institute for Marine and Antarctic Studies Ecology & Biodiversity Centre University of Tasmania Hobart Tasmania Australia Graduate Program in Oceanography Department of Oceanography Faculty of Natural Scienc

Motivation Here, we make available a second version of the BioTIME database, which compiles records of abundance estimates for species in sample events of ecological assemblages through time. The updated version expands version 1.0 of the database by doubling the number of studies and includes substantial additional curation to the taxonomic accuracy of the records, as well as the metadata. Moreover, we now provide an R package (BioTIMEr) to facilitate use of the database. Main Types of Variables Included The database is composed of one main data table containing the abundance records and 11 metadata tables. The data are organised in a hierarchy of scales where 11,989,233 records are nested in 1,603,067 sample events, from 553,253 sampling locations, which are nested in 708 studies. A study is defined as a sampling methodology applied to an assemblage for a minimum of 2 years. Spatial Location and Grain Sampling locations in BioTIME are distributed across the planet, including marine, terrestrial and freshwater realms. Spatial grain size and extent vary across studies depending on sampling methodology. We recommend gridding of sampling locations into areas of consistent size. Time Period and Grain The earliest time series in BioTIME start in 1874, and the most recent records are from 2023. Temporal grain and duration vary across studies. We recommend doing sample-level rarefaction to ensure consistent sampling effort through time before calculating any diversity metric. Major Taxa and Level of Measurement The database includes any eukaryotic taxa, with a combined total of 56,400 taxa. Software Format csv and. SQL.

关键词： assemblage biodiversity community database ecoinformatics species taxa time

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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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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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Soft-Dielectron Excess in Proton-Proton Collisions at s=13 TeV

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Physical Review Letters 2021年第4期127卷 042302-042302页

作者： S. Acharya D. Adamová A. Adler J. Adolfsson M. M. Aggarwal G. Aglieri Rinella M. Agnello N. Agrawal Z. Ahammed S. Ahmad S. U. Ahn Z. Akbar A. Akindinov M. Al-Turany S. N. Alam D. S. D. Albuquerque D. Aleksandrov B. Alessandro H. M. Alfanda R. Alfaro Molina B. Ali Y. Ali A. Alici N. Alizadehvandchali A. Alkin J. Alme T. Alt L. Altenkamper I. Altsybeev M. N. Anaam C. Andrei D. Andreou A. Andronic M. Angeletti V. Anguelov C. Anson T. Antičić F. Antinori P. Antonioli N. Apadula L. Aphecetche H. Appelshäuser S. Arcelli R. Arnaldi M. Arratia I. C. Arsene M. Arslandok A. Augustinus R. Averbeck S. Aziz M. D. Azmi A. Badalà Y. W. Baek S. Bagnasco X. Bai R. Bailhache R. Bala A. Balbino A. Baldisseri M. Ball S. Balouza D. Banerjee R. Barbera L. Barioglio G. G. Barnaföldi L. S. Barnby V. Barret P. Bartalini C. Bartels K. Barth E. Bartsch F. Baruffaldi N. Bastid S. Basu G. Batigne B. Batyunya D. Bauri J. L. Bazo Alba I. G. Bearden C. Beattie C. Bedda N. K. Behera I. Belikov A. D. C. Bell Hechavarria F. Bellini R. Bellwied V. Belyaev G. Bencedi S. Beole A. Bercuci Y. Berdnikov D. Berenyi R. A. Bertens D. Berzano M. G. Besoiu L. Betev A. Bhasin I. R. Bhat M. A. Bhat H. Bhatt B. Bhattacharjee A. Bianchi L. Bianchi N. Bianchi J. Bielčík J. Bielčíková A. Bilandzic G. Biro R. Biswas S. Biswas J. T. Blair D. Blau C. Blume G. Boca F. Bock A. Bogdanov S. Boi J. Bok L. Boldizsár A. Bolozdynya M. Bombara G. Bonomi H. Borel A. Borissov H. Bossi E. Botta L. Bratrud P. Braun-Munzinger M. Bregant M. Broz E. Bruna G. E. Bruno M. D. Buckland D. Budnikov H. Buesching S. Bufalino O. Bugnon P. Buhler P. Buncic Z. Buthelezi J. B. Butt S. A. Bysiak D. Caffarri A. Caliva E. Calvo Villar J. M. M. Camacho R. S. Camacho P. Camerini F. D. M. Canedo A. A. Capon F. Carnesecchi R. Caron J. Castillo Castellanos A. J. Castro E. A. R. Casula F. Catalano C. Ceballos Sanchez P. Chakraborty S. Chandra W. Chang S. Chapeland M. Chartier S. Chattopadhyay A. Chauvin C. Cheshkov B. Cheynis V. Chibante Barroso D. D. Chinellato S. Cho P. Chochula T. Chowdhury P. Chris Variable Energy Cyclotron Centre Homi Bhabha National Institute Kolkata India Nuclear Physics Institute of the Czech Academy of Sciences Řežu Prahy Czech Republic Johann-Wolfgang-Goethe Universität Frankfurt Institut für Informatik Fachbereich Informatik und Mathematik Frankfurt Germany Lund University Department of Physics Division of Particle Physics Lund Sweden Physics Department Panjab University Chandigarh India European Organization for Nuclear Research (CERN) Geneva Switzerland Dipartimento DISAT del Politecnico and Sezione INFN Turin Italy Centro Fermi—Museo Storico della Fisica e Centro Studi e Ricerche “Enrico Fermi’ Rome Italy INFN Sezione di Bologna Bologna Italy Department of Physics Aligarh Muslim University Aligarh India Korea Institute of Science and Technology Information Daejeon Republic of Korea Indonesian Institute of Sciences Jakarta Indonesia NRC «Kurchatov» Institute - ITEP Moscow Russia Research Division and ExtreMe Matter Institute EMMI GSI Helmholtzzentrum für Schwerionenforschung GmbH Darmstadt Germany Fudan University Shanghai China Universidade Estadual de Campinas (UNICAMP) Campinas Brazil National Research Centre Kurchatov Institute Moscow Russia INFN Sezione di Torino Turin Italy Central China Normal University Wuhan China Instituto de Física Universidad Nacional Autónoma de México Mexico City Mexico COMSATS University Islamabad Islamabad Pakistan Dipartimento di Fisica e Astronomia dell’Università Bologna Italy Sezione INFN Bologna Italy University of Houston Houston Texas USA Bogolyubov Institute for Theoretical Physics National Academy of Sciences of Ukraine Kiev Ukraine Department of Physics and Technology University of Bergen Bergen Norway Institut für Kernphysik Johann Wolfgang Goethe-Universität Frankfurt Frankfurt Germany St. Petersburg State University St. Petersburg Russia Horia Hulubei National Institute of Physics and Nuclear Engineering Bucharest Romania Westfälische Wilhelms-Universität Münster In

A measurement of dielectron production in proton-proton (pp) collisions at s=13 TeV, recorded with the ALICE detector at the CERN LHC, is presented in this Letter. The data set was recorded with a reduced magnetic solenoid field. This enables the investigation of a kinematic domain at low dielectron (ee) invariant mass mee and pair transverse momentum pT,ee that was previously inaccessible at the LHC. The cross section for dielectron production is studied as a function of mee, pT,ee, and event multiplicity dNch/dη. The expected dielectron rate from hadron decays, called hadronic cocktail, utilizes a parametrization of the measured η/π0 ratio in pp and proton-nucleus collisions, assuming that this ratio shows no strong dependence on collision energy at low transverse momentum. Comparison of the measured dielectron yield to the hadronic cocktail at 0.15

关键词： High-energy accelerators & colliders

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Elliptic Flow of Electrons from Beauty-Hadron Decays in Pb-Pb Collisions at sNN=5.02 TeV

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Physical Review Letters 2021年第16期126卷 162001-162001页

作者： S. Acharya D. Adamová A. Adler J. Adolfsson M. M. Aggarwal G. Aglieri Rinella M. Agnello N. Agrawal Z. Ahammed S. Ahmad S. U. Ahn Z. Akbar A. Akindinov M. Al-Turany S. N. Alam D. S. D. Albuquerque D. Aleksandrov B. Alessandro H. M. Alfanda R. Alfaro Molina B. Ali Y. Ali A. Alici N. Alizadehvandchali A. Alkin J. Alme T. Alt L. Altenkamper I. Altsybeev M. N. Anaam C. Andrei D. Andreou A. Andronic M. Angeletti V. Anguelov C. Anson T. Antičić F. Antinori P. Antonioli N. Apadula L. Aphecetche H. Appelshäuser S. Arcelli R. Arnaldi M. Arratia I. C. Arsene M. Arslandok A. Augustinus R. Averbeck S. Aziz M. D. Azmi A. Badalà Y. W. Baek S. Bagnasco X. Bai R. Bailhache R. Bala A. Balbino A. Baldisseri M. Ball S. Balouza D. Banerjee R. Barbera L. Barioglio G. G. Barnaföldi L. S. Barnby V. Barret P. Bartalini C. Bartels K. Barth E. Bartsch F. Baruffaldi N. Bastid S. Basu G. Batigne B. Batyunya D. Bauri J. L. Bazo Alba I. G. Bearden C. Beattie C. Bedda N. K. Behera I. Belikov A. D. C. Bell Hechavarria F. Bellini R. Bellwied V. Belyaev G. Bencedi S. Beole A. Bercuci Y. Berdnikov D. Berenyi R. A. Bertens D. Berzano M. G. Besoiu L. Betev A. Bhasin I. R. Bhat M. A. Bhat H. Bhatt B. Bhattacharjee A. Bianchi L. Bianchi N. Bianchi J. Bielčík J. Bielčíková A. Bilandzic G. Biro R. Biswas S. Biswas J. T. Blair D. Blau C. Blume G. Boca F. Bock A. Bogdanov S. Boi J. Bok L. Boldizsár A. Bolozdynya M. Bombara G. Bonomi H. Borel A. Borissov H. Bossi E. Botta L. Bratrud P. Braun-Munzinger M. Bregant M. Broz E. Bruna G. E. Bruno M. D. Buckland D. Budnikov H. Buesching S. Bufalino O. Bugnon P. Buhler P. Buncic Z. Buthelezi J. B. Butt S. A. Bysiak D. Caffarri A. Caliva E. Calvo Villar J. M. M. Camacho R. S. Camacho P. Camerini F. D. M. Canedo A. A. Capon F. Carnesecchi R. Caron J. Castillo Castellanos A. J. Castro E. A. R. Casula F. Catalano C. Ceballos Sanchez P. Chakraborty S. Chandra W. Chang S. Chapeland M. Chartier S. Chattopadhyay A. Chauvin C. Cheshkov B. Cheynis V. Chibante Barroso D. D. Chinellato S. Cho P. Chochula T. Chowdhury P. Chris Variable Energy Cyclotron Centre Homi Bhabha National Institute Kolkata India Nuclear Physics Institute of the Czech Academy of Sciences Řež u Prahy Czech Republic Johann-Wolfgang-Goethe Universität Frankfurt Institut für Informatik Fachbereich Informatik und Mathematik Frankfurt Germany Lund University Department of Physics Division of Particle Physics Lund Sweden Physics Department Panjab University Chandigarh India European Organization for Nuclear Research (CERN) Geneva Switzerland Dipartimento DISAT del Politecnico and Sezione INFN Turin Italy Centro Fermi-Museo Storico della Fisica e Centro Studi e Ricerche “Enrico Fermi ” Rome Italy INFN Sezione di Bologna Bologna Italy Department of Physics Aligarh Muslim University Aligarh India Korea Institute of Science and Technology Information Daejeon Republic of Korea Indonesian Institute of Sciences Jakarta Indonesia NRC «Kurchatov» what Institute-ITEP Moscow Russia Research Division and ExtreMe Matter Institute EMMI GSI Helmholtzzentrum für Schwerionenforschung GmbH Darmstadt Germany Fudan University Shanghai China Universidade Estadual de Campinas (UNICAMP) Campinas Brazil National Research Centre Kurchatov Institute Moscow Russia INFN Sezione di Torino Turin Italy Central China Normal University Wuhan China Instituto de Física Universidad Nacional Autónoma de México Mexico City Mexico COMSATS University Islamabad Islamabad Pakistan Dipartimento di Fisica e Astronomia dell’Università Bologna Italy Sezione INFN Bologna Italy University of Houston Houston Texas USA Bogolyubov Institute for Theoretical Physics National Academy of Sciences of Ukraine Kiev Ukraine Department of Physics and Technology University of Bergen Bergen Norway Institut für Kernphysik Johann Wolfgang Goethe-Universität Frankfurt Frankfurt Germany St. Petersburg State University St. Petersburg Russia Horia Hulubei National Institute of Physics and Nuclear Engineering Bucharest Romania Westfälische Wilhelms-Universität Münster

The elliptic flow of electrons from beauty hadron decays at midrapidity (|y|<0.8) is measured in Pb-Pb collisions at sNN=5.02 TeV with the ALICE detector at the LHC. The azimuthal distribution of the particles produced in the collisions can be parametrized with a Fourier expansion, in which the second harmonic coefficient represents the elliptic flow, v2. The v2 coefficient of electrons from beauty hadron decays is measured for the first time in the transverse momentum (pT) range 1.3–6 GeV/c in the centrality class 30%–50%. The measurement of electrons from beauty-hadron decays exploits their larger mean proper decay length cτ≈500 μm compared to that of charm hadrons and most of the other background sources. The v2 of electrons from beauty hadron decays at midrapidity is found to be positive with a significance of 3.75 σ. The results provide insights into the degree of thermalization of beauty quarks in the medium. A model assuming full thermalization of beauty quarks is strongly disfavored by the measurement at high pT, but is in agreement with the results at low pT. Transport models including substantial interactions of beauty quarks with an expanding strongly interacting medium describe the measurement within uncertainties.

关键词： Photon, lepton & quark production

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