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

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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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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26th Annual Computational Neuroscience Meeting (CNS*2017) of the Organization for Computational Neuroscience Antwerp, Belgium, July 15-20, 2017

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 59-59页

作者： [Anonymous] Indiana University Purdue University Indianapolis Indianapolis IN 46032 USA Stark Neurosciences Research Institute Indiana University School of Medicine Indianapolis IN 46032 USA Department of Mathematics East Carolina University Greenville NC 27858 USA Jülich Supercomputing Centre Forschungszentrum Jülich 52425 Jülich Germany Future Systems Swiss National Supercomputing Centre 8092 Zurich Switzerland User Engagement and Support Swiss National Supercomputing Centre 6900 Lugano Switzerland Institut de Neurosciences des Systèmes Aix Marseille Univ 13005 Marseille France Simulation Lab Neuroscience Forschungszentrum Jülich Jülich Germany Department of Experimental Psychology Ghent University 9000 Ghent Belgium Donders Center for Cognitive Neuroimaging Radboud University 6525HR Nijmegen The Netherlands Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO 80309 USA Department of Neurosurgery Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Neurology Johns Hopkins School of Medicine Baltimore MD 21287 USA Department of Otolaryngology Johns Hopkins School of Medicine Baltimore MD 21287 USA INSERM U968 Paris France Sorbonne Universités UPMC University Paris 06 UMR_S 968 Institut de la Vision Paris France CNRS UMR_7210 Paris France Department of Computer Architecture and Technology University of Granada (CITIC) Granada Spain Sorbonne Universités UPMC Univ Paris 06 INSERM CNRS Institut de la Vision Paris France Department of Adaptive Machine Systems Osaka University Osaka Japan Department of Computer Science University of Cergy-Pontoise Cergy-Pontoise France Department of Physics and Astronomy College of Charleston Charleston SC 29424 USA School of Physics Faculty of Science University of Sydney Sydney NSW 2006 Australia Center of Excellence for Integrative Brain Function Australian Research Council Sydney Australia Max Planck Institute for Human Cognitive and Brain Sciences Saxony Lei

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Highlights from the 11th ISCB Student Council Symposium 2015. Dublin, Ireland. 10 July 2015

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BMC bioinformatics 2016年第3期17 Suppl 3卷 95页

作者： Katie Wilkins Mehedi Hassan Margherita Francescatto Jakob Jespersen R. Gonzalo Parra Bart Cuypers Dan DeBlasio Alexander Junge Anupama Jigisha Farzana Rahman Griet Laenen Sander Willems Lieven Thorrez Yves Moreau Nagarajan Raju Sonia Pankaj Chothani C. Ramakrishnan Masakazu Sekijima M. Michael Gromiha Paddy J Slator Nigel J Burroughs Przemysław Szałaj Zhonghui Tang Paul Michalski Oskar Luo Xingwang Li Yijun Ruan Dariusz Plewczynski Giulia Fiscon Emanuel Weitschek Massimo Ciccozzi Paola Bertolazzi Giovanni Felici Pieter Meysman Manu Vanaerschot Maya Berg Hideo Imamura Jean-Claude Dujardin Kris Laukens Westa Domanova James R. Krycer Rima Chaudhuri Pengyi Yang Fatemeh Vafaee Daniel J. Fazakerley Sean J. Humphrey David E. James Zdenka Kuncic Plant Pathology and Plant-Microbe Biology Section School of Integrative Plant Science Cornell University Ithaca USA Graduate Field of Computational Biology Cornell University Ithaca USA School of Computing & Mathematics University of South Wales Cardiff UK Department of Genome Biology for Neurodegenerative Diseases German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association ᅟ Germany Department of Surgery Massachusetts General Hospital The Broad Institute of MIT and Harvard Boston USA Department of Systems Biology Technical University of Denmark Kemitorvet Denmark Protein Physiology Lab Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires Buenos Aires Argentina Molecular Parasitology Unit (MPU) Institute of Tropical Medicine Antwerp Belgium Advanced Database Research and Modeling (ADReM) research group University of Antwerp Antwerpen Belgium Department of Computer Science University of Arizona Tucson USA Department of Veterinary Clinical and Animal Sciences Center for non-coding RNA in Technology and Health University of Copenhagen Copenhagen Denmark University College Dublin Dublin Ireland Department of Electrical Engineering (ESAT) STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Minds Medical IT Department Leuven Belgium Scientific Institute of Public Health (WIV-ISP) Platform of Biotechnology and Molecular Biology (PBB) Brussels Belgium Department of Development and Regeneration @ Kulak KU Leuven Kortrijk Belgium Department of Biotechnology Bhupat and Jyoti Metha School of Biosciences Indian Institute of Technology Madras Chennai India Philips Research North America Briarcliff Manor USA Global Scientific Information and Computing Center (GSIC) Tokyo Institute of Technology Tokyo Japan Systems Biology Centre University of Warwick Senate House Coventry UK Systems Biology Doctoral Training Centre University of Warwick Senate House Coventry UK Center for B

A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana Rahman O1 Prioritizing a drug’s targets using both gene expression and structural similarity Griet Laenen, Sander Willems, Lieven Thorrez, Yves Moreau O2 Organism specific protein-RNA recognition: A computational analysis of protein-RNA complex structures from different organisms Nagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael Gromiha O3 Detection of Heterogeneity in Single Particle Tracking Trajectories Paddy J Slator, Nigel J Burroughs O4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecture Przemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz Plewczynski O5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classification Giulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni Felici O6 A systems Biology Compendium for Leishmania donovani Bart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris Laukens O7 Unravelling signal coordination from large scale phosphorylation kinetic data Westa Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic

关键词： Visceral Leishmaniasis Feature Selection Method Frequent Itemset Mining Leishmania Donovani Student Council

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18th European Symposium on Radiopharmacy and Radiopharmaceuticals Salzburg, Austria. 7-10 April 2016

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EJNMMI RADIOPHARMACY AND CHEMISTRY 2016年第1期1卷 1-37页

作者： [Anonymous] Los Alamos National Laboratory Los Alamos USA Oak Ridge National Laboratory Oak Ridge USA Department of Nuclear Medicine Medical University Innsbruck Innsbruck Austria Department of Radiology & Nuclear Medicine Radboud University Medical Center Nijmegen The Netherlands Institute of Molecular and Translational Medicine Faculty of Medicine and Dentistry Palacky University Olomouc Czech Republic Département de Médecine Nucléaire et Radiobiologie Faculté de Médecine et Sciences de la Santé Université de Sherbrooke Sherbrooke Canada Centre d’Imagerie Moléculaire de Sherbrooke (CIMS) CR-CHUS Sherbrooke Canada Division of Molecular Biology/Biocenter Medical University Innsbruck Innsbruck Austria Department of Nuclear Medicine Radboud University Medical Center Nijmegen The Netherlands IENI-CNR Padua Italy DiSCOG-University of Padua Padua Italy IOV Padua Padua Italy IC-CNR Bari Italy IBB-CNR Naples Italy Laboratory of Radiopharmacy KU Leuven Leuven Belgium Micro Flow Chemistry & Process Technology Chemical Engineering and Chemistry Department TU Eindhoven Eindhoven The Netherlands Laboratory for Radiopharmacy University of Leuven Leuven Belgium Department of Nuclear Medicine and Molecular Imaging University of Leuven Leuven Belgium Department of Medicine and Surgery Tecnomed Foundation University of Milano-Bicocca Milan Italy Dipartimento di Biotecnologie Mediche e Medicina Traslazionale Università degli Studi di Milano Milan Italy Department of Radiology & Nuclear Medicine VU University Medical Center Amsterdam The Netherlands Department of Clinical Pharmacology & Pharmacy VU University Medical Center Amsterdam The Netherlands Université de Lorraine Vandoeuvre les Nancy France NancycloTEP Plateforme d’imagerie expérimentale Vandoeuvre les Nancy France CNRS UMR 7565 SRSMC Vandoeuvre les Nancy France CHU de Nancy-Brabois Vandoeuvre les Nancy France Department of Biomedical Imaging and Image-guided Therapy Division of Nuclear Medicine Medical Univers

Table of contents OP03 Selective extraction of medically-related radionuclides from proton-irradiated thorium targets V. Radchenko, J.W. Engle, C. Roy, J. Griswold, M.F. Nortier, E.R. Birnbaum, M. Brugh, S. Mirzadeh, K. D. John, M.E. Fassbender OP04 Comparison of [68Ga]FSC(succ-RGD)3 and [68Ga]NODAGA-RGD for PET imaging of alpha v beta 3 integrin expression Chuangyan Zhai, Gerben M. Franssen, Milos Petrik, Peter Laverman, Clemens Decristoforo OP05 A new NPY-Y1R targeting peptide for breast cancer PET imaging Ait-Mohand Samia, Dumulon-Perreault Veronique, Guerin Brigitte OP06 The influence of multivalency on CCK 2 receptor targeting D. Summer, A. Kroess, C. Rangger, H. Haas, P. Laverman, F. Gerben, E. von Guggenberg, *** OP07 SPECT Imaging of alpha v beta 3 Expression by [99mTc(N)PNP43]- Bifunctional Chimeric RGD Peptide not Cross-Reacting with alpha v beta 5 Cristina Bolzati, Nicola Salvarese, Fiorenzo Refosco, Laura Melendez-Alafort, Debora Carpanese, Antonio Rosato, Michele Saviano, Annarita Del Gatto, Daniela Comegna, Laura Zaccaro OP09 New dienophiles for the inverse-electron-demand Diels-Alder reaction and for pretargeted PET imaging Emilie Billaud, Muneer Ahamed, Frederik Cleeren, Elnaz Shahbazali, Tim Noel, Volker Hessel, Alfons Verbruggen and Guy Bormans OP10 New complexing agent for Al18F-labelling of heat-sensitive biomolecules: Synthesis and preclinical evaluation of Al18F-RESCA1-HAS Cleeren F, Lecina J, Koole M, Verbruggen A and Bormans G OP11 A novel versatile precursor efficient for F-18 radiolabelling via click-chemistry B. Lugatoa, S. Stucchia, E.A. Turollaa, L. Giulianoa, ***, P. Ferraboschib OP12 A general applicable method to quantify unidentified UV impurities in radiopharmaceuticals R.P. Klok, M.P.J. Mooijer, N.H. Hendrikse, A.D. Windhorst OP13 Development of [F-18]Fluoro-C-glycosides to radiolabel peptides Collet C., Petry N., Chretien F., Karcher G., Pellegrini-Moise N., Lamande-Langle S. OP14 A Microfluidic Approach for the 68

关键词： Positron Emission Tomography Single Photon Emission Compute Tomography Standard Uptake Value Positron Emission Tomography Imaging High Pressure Liquid Chromatography

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Quad Rotorcraft Control: Vision-Based Hovering and Navigation 2013

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丛书名： Advances in Industrial Control

2012年

作者： Luis Rodolfo García Carrillo Alejandro Enrique Dzul López Rogelio Lozano Claude Pégard

ISBN: (纸本)1447143981;9781447143987

Quad Rotorcraft Control develops original control methods for the navigation and hovering flight of an autonomous mini-quad-rotor robotic helicopter. These methods use an imaging system and a combination of inertial and altitude sensors to localize and guide the movement of the unmanned aerial vehicle relative to its immediate environment. The history, classification and applications of UAVs are introduced, followed by a description of modelling techniques for quad-rotor's and the experimental platform itself. A control strategy for the improvement of attitude stabilization in quad-rotor's is then proposed and tested in real-time experiments. The strategy, based on the use low-cost components and with experimentally-established robustness, avoids drift in the UAV's angular position by the addition of an internal control loop to each electronic speed controller ensuring that, during hovering flight, all four motors turn at almost the same speed. The quad-rotor's Euler angles being very close to the origin, other sensors like GPS or image-sensing equipment can be incorporated to perform autonomous positioning or trajectory-tracking tasks. Two vision-based strategies, each designed to deal with a specific kind of mission, are introduced and separately tested. The first stabilizes the quad-rotor over a landing pad on the ground; it extracts the 3-dimensional position using homography estimation and derives translational velocity by optical flow calculation. The second combines colour-extraction and line-detection algorithms to control the quad-rotor's 3-dimensional position and achieves forward velocity regulation during a road-following task. In order to estimate the translational-dynamical characteristics of the quad-rotor (relative position and translational velocity) as they evolve within a building or other unstructured, GPS-deprived environment, imaging, inertial and altitude sensors are combined in a state observer. The text give the reader a current view of the

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Analysis of a "meta - Trade study" interpretation of decision-making with a value proposition for space programs

Analysis of a "meta - Trade study" interpretation of decisio...

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Space 2006 Conference

作者： Rockower, Edward B. Lockheed Martin Space Systems Company Sunnyvale CA 94089 United States Advanced Technology Center Modeling Simulation and Information Science

ISBN: (纸本)1563478242

Tightening budgets and greater competition for funding are increasing the need to more completely, persuasively, and transparently value and market complex, and often exotic, Space Programs. This is driving an expanding view of what's required in an engineering, economic, and political language of discourse. Words and phrases like holistic, future generations, new frontiers, vision, inspiring, and sustainable are increasingly important to encompass the full range of stakeholders, the full spectrum of societal needs and values, and the vastly differing awareness, sophistication, and priorities among stakeholders. There's a well-known saying in Sales, that "you sell the sizzle, not the steak". This is increasingly necessary to achieve widespread understanding, public buy-in, and sustainability. We consider how the components of a "value proposition" may be mapped to corresponding parts of the final report for a kind of "Meta - Trade Study" with respect to allocation of Society's resources among alternative objectives and programs. We investigate how that viewpoint helps us to understand, quantify and communicate a "Value Proposition for Space". We also point out limitations of this perspective, hence areas that must be extended, and suggest how this may be done. Copyright © 2006 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

关键词： Space research

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The environmental data coding specification and its SISOl role

The environmental data coding specification and its SISOl ro...

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2005 Spring Simulation Interoperability Workshop, SIW 2005

作者： Richbourg, Robert F. Janett, Annette Moore, Ronald G. Jodeit, David Dobey, Virginia T. Foley, Paul G. Institute for Defense Analyses 4850 Mark Center Drive AlexandriaVA2311-1882 United States Lockheed-Martin Information Systems Advanced Simulation Center 3605 - 132nd Avenue SE Suite 400 BellevueWA90006 United States Science Applications International Corporation 5301 Bolsa Avenue Huntington BeachCA92647 United States ITT Industries 2560 Huntington Avenue AlexandriaVA22303 United States Science Applications International Corporation 1901 North Beauregard St. Suite 500 AlexandriaVA22311 United States National Geospatial - Intelligence Agency 14675 Lee Road ChantillyVA20151 United States

Digital representations of the physical environment continue to be in great demand, an established trend that appears likely to extend well into the future. Acquiring, enhancing, and processing source information into formats suitable for application use also continue to require significant investment in database generation time and cost, providing a strong motivation for reuse of extant data. Further, federation of disparate systems, each potentially having their own environmental representation, is becoming more commonplace. Both data reuse and system federation depend on the unambiguous communication of environmental objects, properties, and their conditions as a prerequisite for success. The Environmental Data Coding Specification (EDCS) was initiated as a part of the SEDRIS project to address this need across a very wide domain of applicability. During development, the EDCS has been under review by the International Organization for Standardization (ISO) and International Electrotechnical Commission (IEC) for possible adoption as an international standard for a set of dictionaries of environmental data. Concurrently, a Simulation Interoperability Standards Organization (SISO) Product Development Group (PDG) has been both participating in the EDCS development and assessing the potential of ISO/IEC EDCS standard to serve as an interoperability standard for the SISO community. The PDG vision has been focused on endorsing or rejecting the EDCS at the time that the ISO/IEC Editing Committee produced the version that would be accepted or rejected as an international standard. The Final Draft International Standard (FDIS) EDCS, has been produced, submitted for ISO/IEC ballot, and favorably voted for publication as an ISO/IEC information Technology Standard. This paper presents an overview of the recently approved ISO/IEC EDCS and all dictionaries that comprise the specification. We also discuss the EDCS suitability as a standard for data interchange, illustrated by re

关键词： Specifications

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Optimal control of wireless sensor networks for structural health monitoring

Optimal control of wireless sensor networks for structural h...

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Collection of Technical Papers - AIAA 1st Intelligent systems Technical Conference

作者： Zimdars, Andrew L. Bose, Prasanta Lockheed Martin Space Systems Company Advanced Technology Center 1111 Lockheed Martin Way Sunnyvale CA 94089 United States Modeling Simulation and Information Sciences Building 153 Column 2J4 United States

ISBN: (纸本)156347719X

Optimal control of large sensor networks for structural health monitoring requires efficient management of limited energy, network capacity, and computational power. These netorks must accommodate "typical" changes in the host structure and the sensor network, while detecting and responding to anomalous conditions. We treat wireless sensor networks as distributed agents that observe the current state of their environment, choose an action, and receive a vector of reward data encoding the designer's goals for the network. In this setting, the control problem becomes a Markov decision process (MDP) in which the agent acts to maximize the discounted sum of rewards it receives over time, and derives an optimal controller by iteratively improving its policy. The data structures, update rule, and decision procedure that we present exploit the generalized distributive law (GDL), an algebraic formalism that implements tree-structured computations by passing messages between nodes in a tree-structured network. Each node in the network receives a reward signal for its actions, and the coordination procedures specified by the GDL insure that each node chooses an optimal action given its neighbors' decisions. We describe an update procedure for distributed agents so that the network's distributed control law converges by reinforcement learning to a globally optimal solution using only local estimators. We also describe several modifications to the basic junction tree reinforcement learning algorithm that make it more practical to implement in low-power, limited-memory devices. © 2004 by Lockheed Martin Space systems Company.

关键词： Telecommunication networks

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