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Publisher Correction: Multicolor multiscale brain imaging with chromatic multiphoton serial microscopy

Nature communications 2019年第1期10卷 2160页

作者： Lamiae Abdeladim Katherine S Matho Solène Clavreul Pierre Mahou Jean-Marc Sintes Xavier Solinas Ignacio Arganda-Carreras Stephen G Turney Jeff W Lichtman Anatole Chessel Alexis-Pierre Bemelmans Karine Loulier Willy Supatto Jean Livet Emmanuel Beaurepaire Laboratory for Optics and Biosciences Ecole polytechnique CNRS INSERM IP Paris Palaiseau 91128 France. Sorbonne Université INSERM CNRS Institut de la Vision 17 rue Moreau Paris 75012 France. Cold Spring Harbor Laboratory Cold Spring Harbor 11724 NY USA. Department of Computer Science and Artificial Intelligence University of the Basque Country San Sebastian 20018 Spain. IKERBASQUE Basque Foundation for Science Bilbao 48013 Spain. Donostia International Physics Center (DIPC) San Sebastian 20018 Spain. Center for Brain Science and Department of Molecular and Cellular Biology Harvard University Cambridge 02138 MA USA. Neurodegenerative Diseases Laboratory Molecular Imaging Research Center Institut de Biologie François Jacob CEA CNRS Université Paris-Sud Fontenay-aux-Roses 92265 France. Sorbonne Université INSERM CNRS Institut de la Vision 17 rue Moreau Paris 75012 France. jean.livet@inserm.fr. Laboratory for Optics and Biosciences Ecole polytechnique CNRS INSERM IP Paris Palaiseau 91128 France. emmanuel.beaurepaire@polytechnique.edu.

Affiliation 4 incorrectly read 'University of the Basque Country (Ikerbasque), University of the Basque Country and Donostia International Physics Center, San Sebastian 20018, Spain.'Also, the affiliations of Ignacio Arganda-Carreras with 'IKERBASQUE, Basque Foundation for Science, Bilbao, 48013, Spain' and 'Donostia International Physics Center (DIPC), San Sebastian, 20018, Spain' were inadvertently ***, the third sentence of the first paragraph of the Results section entitled 'Multicontrast organ-scale imaging with ChroMS microscopy' incorrectly read 'For example, one can choose lambda1 = 850 and lambda2 = 110 nm for optimal two-photon excitation of blue and red chromophores.'. The correct version reads 'lambda2 = 1100 nm' instead of 'lambda2 = 110 nm'. These errors have now been corrected in the PDF and HTML versions of the Article.

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Studying bioluminescence flashes with the ANTARES deep Sea neutrino telescope

arXiv

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arXiv 2021年

作者： Reeb, Nico Hutschenreuter, S. Zehetner, P. Ensslin, T. Albert, A. Alves, S. André, M. Anghinolfi, M. Anton, G. Ardid, M. Aubert, J.-J. Aublin, J. Baret, B. Basa, S. Belhorma, B. Bendahman, M. Bertin, V. Biagi, S. Bissinger, M. Boumaaza, J. Bouta, M. Bouwhuis, M.C. Brânzaş, H. Bruijn, R. Brunner, J. Busto, J. Caiffi, B. Capone, A. Caramete, L. Carr, J. Carretero, V. Celli, S. Chabab, M. Chau, T.N. Chiarusi, T. Circella, M. Coleiro, A. Colomer-Molla, M. Coniglione, R. Coyle, P. Creusot, A. Díaz, A.F. de Wasseige, G. Deschamps, A. Distefano, C. Di Palma, I. Domi, A. Donzaud, C. Dornic, D. Drouhin, D. van Eeden, T. Enzenhöfer, A. Fermani, P. Ferrara, G. Filippini, F. Fusco, L. Gatelet, Y. Gay, P. Glotin, H. Gozzini, R. Ruiz, R. Gracia Graf, K. Guidi, C. Hallmann, S. van Haren, H. Heijboer, A.J. Hello, Y. Hernández-Rey, J.J. Hößl, J. Hofestädt, J. Huang, F. Illuminati, G. James, C.W. Jisse-Jung, B. de Jong, M. de Jong, P. Jongen, M. Kadler, M. Kalekin, O. Katz, U. Khan-Chowdhury, N.R. Kouchner, A. Kreykenbohm, I. Kulikovskiy, V. Lahmann, R. Le Breton, R. Lefèvre, D. Leonora, E. Levi, G. Lincetto, M. Lopez-Coto, D. Loucatos, S. Maderer, L. Manczak, J. Marcelin, M. Margiotta, A. Marinelli, A. Martínez-Mora, J.A. Melis, K. Migliozzi, P. Moussa, A. Muller, R. Nauta, L. Navas, S. Nezri, E. Fearraigh, B.Ó. Organokov, M. Pavalaş, G.E. Pellegrino, C. Perrin-Terrin, M. Piattelli, P. Pieterse, C. Poirè, C. Popa, V. Pradier, T. Randazzo, N. Reck, S. Riccobene, G. Romanov, A. Sánchez-Losa, A. Greus, F. Salesa Samtleben, D.F.E. Sanguineti, M. Sapienza, P. Schnabel, J. Schumann, J. Schüssler, F. Spurio, M. Stolarczyk, Th. Taiuti, M. Tingay, S.J. Vallage, B. van Elewyck, V. Versari, F. Viola, S. Vivolo, D. Wilms, J. Zavatarelli, S. Zegarelli, A. Zornoza, J.D. Zúñiga, J. Information Field Theory Group Max Planck Institute for Astrophysics Garching Germany Informatics 6 Chair of Robotics Artificial Intelligence and Real time Systems Technical University of Munich Garching Germany Department of Astrophysics IMAPP Radboud University Nijmegen Nijmegen Netherlands Department of Physics Ludwig-Maximilians University Munich Germany CERN Geneva Switzerland Université de Strasbourg CNRS IPHC UMR 7178 StrasbourgF-67000 France Université de Haute Alsace MulhouseF-68200 France IFIC - Instituto de Física Corpuscular CSIC Universitat de València c/ Catedrático José Beltrán 2 Paterna ValenciaE-46980 Spain Technical University of Catalonia Laboratory of Applied Bioacoustics Rambla Exposició Vilanova i la Geltrú Barcelona08800 Spain INFN - Sezione di Genova Via Dodecaneso 33 Genova16146 Italy Friedrich-Alexander-Universität Erlangen-Nürnberg Erlangen Centre for Astroparticle Physics Erwin-Rommel-Str. 1 Erlangen91058 Germany Universitat Politècnica de València C/ Paranimf 1 Gandia46730 Spain Aix Marseille Univ CNRS IN2P3 CPPM Marseille France Université de Paris CNRS Astroparticule et Cosmologie ParisF-75013 France Aix Marseille Univ CNRS CNES LAM Marseille France National Center for Energy Sciences and Nuclear Techniques B.P.1382 RabatR. P. 10001 Morocco University Mohammed V in Rabat Faculty of Sciences 4 av. Ibn Battouta B.P. 1014 R.P. Rabat10000 Morocco Via S. Sofia 62 Catania95123 Italy University Mohammed I Laboratory of Physics of Matter and Radiations B.P.717 Oujda6000 Morocco Nikhef Science Park Amsterdam Netherlands Institute of Space Science Bucharest MagureleRO-077125 Romania Universiteit van Amsterdam Instituut voor Hoge-Energie Fysica Science Park 105 Amsterdam1098 XG Netherlands INFN - Sezione di Roma P.le Aldo Moro 2 Roma00185 Italy Dipartimento di Fisica Università La Sapienza P.le Aldo Moro 2 Roma00185 Italy LPHEA Faculty of Science - Semlali Cadi Ayyad University P.O

We develop a novel technique to exploit the extensive data sets provided by underwater neutrino telescopes to gain information on bioluminescence in the deep sea. The passive nature of the telescopes gives us the unique opportunity to infer information on bioluminescent organisms without actively interfering with them. We propose a statistical method that allows us to reconstruct the light emission of individual organisms, as well as their location and movement. A mathematical model is built to describe the measurement process of underwater neutrino telescopes and the signal generation of the biological organisms. The Metric Gaussian Variational Inference algorithm is used to reconstruct the model parameters using photon counts recorded by the neutrino detectors. We apply this method to synthetic data sets and data collected by the ANTARES neutrino telescope. The telescope is located 40 km off the French coast and fixed to the sea floor at a depth of 2475 m. The runs with synthetic data reveal that we can reliably model the emitted bioluminescent flashes of the organisms. Furthermore, we find that the spatial resolution of the localization of light sources highly depends on the configuration of the telescope. Precise measurements of the efficiencies of the detectors and the attenuation length of the water are crucial to reconstruct the light emission. Finally, the application to ANTARES data reveals the first precise localizations of bioluminescent organisms using neutrino telescope data. © 2021, CC BY.

关键词： Bioluminescence

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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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Panel position statements 3

Panel position statements

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3rd International Symposium on Foundations of Health Information Engineering and Systems, FHIES 2013

作者： Dube, Kudakwashe Moodley, Deshendran Thies, Bill Liu, Jane W.S Cafazzo, Joseph Sokolsky, Oleg School of Engineering and Advanced Technology Massey University New Zealand UKZN/CSIR Meraka Centre for Artificial Intelligence Research and Health Architecture Laboratory School of Mathematics Statistics and Computer Science University of KwaZulu-Natal Durban South Africa Microsoft Research India India Institute of Information Science Academia Sinica Taipei Taiwan Centre for Global eHealth Innovation Canada Department of Computer and Information Science University of Pennsylvania United States

ISBN: (纸本)9783642539558

The western world enjoys a far greater degree of sophistication in computer technology than the developing world; challenges include the fact that infrastructure and resources in the developing world lag far behind; education to use and maintain the technology is often lacking; and cultural and societal issues prohibit its use. Questions include: What is the role of the first world in promoting more widespread use of technology for health informatics? What are the advantages to the first world in promoting more widespread use? What is the role of scientists in the first world in developing technology suitable for less technologically savvy regions? Should we interfere in cultures that do not use technology as we do? What can we practically expect to positively influence by engaging with developing world? How do we engage with the developing world in a sustainable way? Finally, modern vaccines have made huge differences in health the world over; can we expect similar positive transformation from increased computer/information technology in the developing world?

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Evaluation of fast 2D and 3D medical image retrieval approaches based on image miniatures

Evaluation of fast 2D and 3D medical image retrieval approac...

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2nd MICCAI International Workshop on Medical Content-Based Retrieval for Clinical Decision Support, MCBR-CDS 2011

作者： Donner, René Haas, Sebastian Burner, Andreas Holzer, Markus Bischof, Horst Langs, Georg Computational Image Analysis and Radiology Lab. Department of Radiology Medical University of Vienna Austria Institute for Computer Graphics and Vision Graz University of Technology Austria Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology Cambridge MA United States

ISBN: (纸本)9783642284595

The present work evaluates four medical image retrieval approaches based on features derived from image miniatures. We argue that due to the restricted domain of medical image data, the standardized acquisition protocols and the absence of a potentially cluttered background a holistic image description is sufficient to capture high-level image similarities. We compare four different miniature 2D and 3D descriptors and corresponding metrics, in terms of their retrieval performance: (A) plain miniatures together with euclidean distances in a k Nearest Neighbor based retrieval backed by kD-trees;(B) correlations of rigidly aligned miniatures, initialized using the kD-tree;(C) distribution fields together with the l1-norm;(D) SIFT-like histogram of gradients using the χ2-distance. We evaluate the approaches on two data sets: the ImageClef 2009 benchmark of 2D radiographs with the aim to categorize the images and a large set of 3D-CTs representing a realistic sample in a hospital PACS with the objective to estimate the location of the query volume. © 2012 Springer-Verlag.

关键词： Medical imaging

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On the performance of Decapod's digital font reconstruction

On the performance of Decapod's digital font reconstruction

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International Conference on Pattern Recognition

作者： Hasan S. M. Al-Khaffaf Faisal Shafait Michael P. Cutter Thomas M. Breuel IUPR Research Group Technische Universität Kaiserslautern Germany Multimedia Analysis and Data Mining Competence Center German Research Center for Artificial Intelligence Germany Computer Vision Laboratory Computer Engineering Department University of California Santa Cruz Germany

This paper presents the current status of Decapod's English font reconstruction. The Potrace algorithm and its parameters that affect glyph shape are examined. The visual fidelity of Decapod's font reconstruction is shown and compared to Adobe ClearScan TM . The font reconstruction details of the two methods are presented. The experiment demonstrates the capabilities of the two methods in reconstructing the font for a synthetic book typeset each time with one of six English fonts, three serif and three sans-serif. For both typefaces, Decapod is able to create a reusable TTF font that is embedded in the generated PDF document.

关键词： Image reconstruction Shape Portable document format Optical character recognition software Visualization Image segmentation Approximation algorithms

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Constraint-driven floorplan repair

Constraint-driven floorplan repair

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Design Automation Conference

作者： M.D. Moffitt A.N. Ng I.L. Markov M.E. Pollack Artificial Intelligence Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA Advanced Computer Architecture Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA

Floorplanning algorithms have traditionally underperformed experienced designers, even when relatively simple interconnect metrics are concerned. However, the sheer scale of modern systems on chip makes an all-manual design flow infeasible. In this paper, we propose a new efficient automated approach to the floorplan repair problem, where a set of violated design constraints are satisfied by applying small changes to an existing rough floorplan. Such a floor-plan can be produced by a human designer, by a scalable placement algorithm, or result from engineering adjustments to a pre-existing floorplan. In all cases, overlapping modules must be separated, and in some instances, modules may need to be repositioned to satisfy other requirements. The algorithmic framework we propose is built upon an expressive graph-based encoding of constraints. While capable of representing floorplans with or without overlapping modules, it can also support the outline of the core area, fixed module locations, region constraints, proximity and alignment constraints, etc. Instead of applying randomized local search in the hope of satisfying these constraints, we track all implications of imposed constraints and resolve violations by invoking gradual modifications to the floor-plan. The primary focus of this paper is on a particularly efficient conflict-directed algorithm for floorplan repair and legalization. It is shown to completely eliminate overlaps from layouts produced by Capo 9.4, Feng Shui 5.1 and APlace 2.01 on IBM-HB benchmarks with hard blocks; typically requiring negligible runtime and increasing interconnect length by only several percent. Furthermore, we are able to generate legal solutions for these instances that surpass previously reported results in wirelength by an average of roughly 7%

关键词： Algorithm design and analysis Laboratories artificial intelligence computer architecture Modems Constraint optimization Design optimization Humans Shape Encoding

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On the uncertainty inequality as applied to discrete signals

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International Journal of Mathematics and Mathematical Sciences 2006年第1期2006卷

作者： Venkatesh, Y.V. Raja, S. Kumar Vidyasagar, G. Computer Vision and Artificial Intelligence Laboratory Department of Electrical Engineering Indian Institute of Science Bangalore 560012 India Department of Electrical and Computer Engineering Faculty of Engineering National University of Singapore Singapore 117576 Singapore

Given a continuous-time bandlimited signal, the Shannon sampling theorem provides an interpolation scheme for exactly reconstructing it from its discrete samples. We analyze the relationship between concentration (or compactness) in the temporal/spectral domains of the (i) continuous-time and (ii) discrete-time signals. The former is governed by the Heisenberg uncertainty inequality which prescribes a lower bound on the product of effective temporal and spectral spreads of the signal. On the other hand, the discrete-time counterpart seems to exhibit some strange properties, and this provides motivation for the present paper. We consider the following problem: for a bandlimited signal, can the uncertainty inequality be expressed in terms of the samples, using the standard definitions of the temporal and spectral spreads of the signal? In contrast with the results of the literature, we present a new approach to solve this problem. We also present a comparison of the results obtained using the proposed definitions with those available in the literature. Copyright © 2006 Hindawi Publishing Corporation. All rights reserved.

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Throat microphone signal for speaker recognition 8

Throat microphone signal for speaker recognition

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8th International Conference on Spoken Language Processing, ICSLP 2004

作者： Shahina, A. Yegnanarayana, B. Kesheorey, M.R. Speech and Vision Laboratory Department of Computer Science and Engg. Indian Institute of Technology Madras Chennai600 036 India Center for Artificial Intelligence and Robotics Bangalore560 001 India

Speaker recognition systems perform better when clean speech signals are used for the task. In the presence of high levels of background noise, speech recorded from a close speaking microphone will be degraded and hence the performance of the speaker recognition system. Use of a transducer held at the throat results in a signal that is clean even in a noisy environment. This paper discusses the prospect of using such signals for speaker recognition. A study of a text-independent speaker recognition system based on features extracted from speech simultaneously recorded using a throat microphone and a close-speaking microphone in clean and simulated noisy conditions is conducted. Autoassociative neural networks are used to model the speaker characteristics based on the vocal tract system and excitation source features represented by weighted linear prediction cepstral coefficients and linear prediction residual, respectively. The results of experimental studies show that the speech collected from the throat microphone can be used for tasks like speaker recognition, especially in noisy conditions.

关键词： Microphones

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Kernel snakes: non-parametric active contour models

Kernel snakes: non-parametric active contour models

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IEEE International Conference on Systems, Man and Cybernetics

作者： W. Abd-Almageed C.E. Smith S. Ramadan Robotics Artificial Intelligence and Vision Laboratory Department of Electrical and Computer Engineering University of New Mexico Albuquerque NM USA

In this paper, a new non-parametric generalized formulation to statistical pressure snakes is presented. We discuss the shortcomings of the traditional pressure snakes. We then introduce a new generic pressure model that alleviates these shortcomings, based on the Bayesian decision theory. Non-parametric techniques are used to obtain the statistical models that drive the snake. We discuss the advantages of using the proposed non-parametric model compared to other parametric techniques. Multi-colored-target tracking is used to demonstrate the performance of the proposed approach. Experimental results show enhanced, real-time performance.

关键词： Kernel Active contours Deformable models Image edge detection Intelligent robots Robot vision systems artificial intelligence Laboratories Bayesian methods Decision theory

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