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Human Factors and Ergonomics Society 2017 International Annual Meeting, HFES 2017

作者： Savoy, April Patel, Himalaya Flanagan, Mindy E. Daggy, Joanne K. Barker, Barry C. Slaven, James E. Porter, Brian W. Russ, Alissa L. Weiner, Michael Center for Health Information and Communication Department of Veterans Affairs Veterans Health Administration Health Services Research and Development Service CIN 13-416 Richard L. Roudebush VA Medical Center IndianapolisIN United States Regenstrief Institute Inc. IndianapolisIN United States Indiana University School of Informatics and Computing RichmondIN United States Indiana University School of Medicine IndianapolisIN United States College of Pharmacy Purdue University West LafayetteIN United States

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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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Gulfs of expectation: eliciting and verifying differences in trust expectations using personas

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Journal of Trust Management 2016年第1期3卷 1-22页

作者： Shamal Faily David Power Ivan Fléchais Department of Computing & Informatics Bournemouth University Poole UK Department of Computer Science University of Oxford Oxford UK

Personas are a common tool used in Human Computer Interaction to represent the needs and expectations of a system’s stakeholders, but they are also grounded in large amounts of qualitative data. Our aim is to make use of this data to anticipate the differences between a user persona’s expectations of a system, and the expectations held by its developers. This paper introduces the idea of gulfs of expectation – the gap between the expectations held by a user about a system and its developers, and the expectations held by a developer about the system and its users. By evaluating these differences in expectation against a formal representation of a system, we demonstrate how differences between the anticipated user and developer mental models of the system can be verified. We illustrate this using a case study where persona characteristics were analysed to identify divergent behaviour and potential security breaches as a result of differing trust expectations.

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Structure of pion photoproduction amplitudes

arXiv

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arXiv 2018年

作者： Mathieu, V. Nys, J. Fernández-Ramírez, C. Hiller Blin, A.N. Jackura, A. Pilloni, A. Szczepaniak, A.P. Fox, G. Theory Center Thomas Jefferson National Accelerator Facility 12000 Jefferson Avenue Newport NewsVA23606 United States Department of Physics and Astronomy Ghent University Belgium Instituto de Ciencias Nucleares Universidad Nacional Autónoma de México Ciudad de México04510 Mexico Institut für Kernphysik & PRISMA Cluster of Excellence Johannes Gutenberg Universität MainzD-55099 Germany Center for Exploration of Energy and Matter Indiana University BloomingtonIN47403 United States Physics Department Indiana University BloomingtonIN47405 United States School of Informatics and Computing Indiana University BloomingtonIN47405 United States

We derive and apply the finite energy sum rules to pion photoproduction. We evaluate the low energy part of the sum rules using several state-of-the-art models. We show how the differences in the low energy side of the sum rules might originate from different quantum number assignments of baryon resonances. We interpret the observed features in the low energy side of the sum rules with the expectation from Regge theory. Finally, we present a model, in terms of a Regge-pole expansion, that matches the sum rules and the high-energy observables. Copyright © 2018, The Authors. All rights reserved.

关键词： Hadrons

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Global analysis of charge exchange meson production at high energies

arXiv

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arXiv 2018年

作者： Nys, J. Hiller Blin, A.N. Mathieu, V. Fernández-Ramírez, C. Jackura, A. Pilloni, A. Ryckebusch, J. Szczepaniak, A.P. Fox, G. Department of Physics and Astronomy Ghent University Belgium Center for Exploration of Energy and Matter Indiana University BloomingtonIN47403 United States Physics Department Indiana University BloomingtonIN47405 United States Institut für Kernphysik & PRISMA Cluster of Excellence Johannes Gutenberg Universität MainzD-55099 Germany Theory Center Thomas Jefferson National Accelerator Facility 12000 Jefferson Avenue Newport NewsVA23606 United States Instituto de Ciencias Nucleares Universidad Nacional Autónoma de México Ciudad de México04510 Mexico School of Informatics and Computing Indiana University BloomingtonIN47405 United States

Many experiments that are conducted to study the hadron spectrum rely on peripheral resonance production. Hereby, the rapidity gap allows the process to be viewed as an independent fragmentation of the beam and the target, with the beam fragmentation dominated by production and decays of meson resonances. We test this separation by determining the kinematic regimes that are dominated by factorizable contributions, indicating the most favorable regions to perform this kind of experiments. In doing so, we use a Regge model to analyze the available world data of charge exchange meson production with beam momentum above 5 GeV in the laboratory frame, that are not dominated by either pion or Pomeron exchanges. We determine the Regge residues and point out the kinematic regimes which are dominated by factorizable contributions. Copyright © 2018, The Authors. All rights reserved.

关键词： Charge transfer

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Nearly optimal sparse group testing

arXiv

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arXiv 2017年

作者： Gandikota, Venkata Grigorescu, Elena Jaggi, Sidharth Zhou, Samson Department of Computer Science Johns Hopkins University BaltimoreMD United States Department of Computer Science Purdue University West LafayetteIN United States Department of Information Engineering Chinese University of Hong Kong Shatin N.T. Hong Kong School of Informatics Computing and Engineering Indiana University BloomingtonIN United States

Group testing is the process of pooling arbitrary subsets from a set of n items so as to identify, with a minimal number of tests, a "small" subset of d defective items. In "classical" non-adaptive group testing, it is known that when d is substantially smaller than n, Θ(d log(n)) tests are both information-theoretically necessary and sufficient to guarantee recovery with high probability. Group testing schemes in the literature meeting this bound require most items to be tested Ω(log(n)) times, and most tests to incorporate Ω(n/d) items. Motivated by physical considerations, we study group testing models in which the testing procedure is constrained to be "sparse". Specifically, we consider (separately) scenarios in which (a) items are finitely divisible and hence may participate in at most γ ∈ o(log(n)) tests;or (b) tests are size-constrained to pool no more than ρ ∈ o(n/d)items per test. For both scenarios we provide information-theoretic lower bounds on the number of tests required to guarantee high probability recovery. In particular, one of our main results shows that γ-finite divisibility of items forces any non-adaptive group testing algorithm with probability of recovery error at most ϵ to perform at least γd(n/d)(1-5ϵ)/γ tests. Analogously, for ρ-sized constrained tests, we show an information-theoretic lower bound of Ω(n/ρ) tests - hence in both settings the number of tests required grow dramatically (relative to the classical setting) as a function of n. In both scenarios we provide both randomized constructions (under both ϵ-error and zero-error reconstruction guarantees) and explicit constructions of designs with computationally efficient reconstruction algorithms that require a number of tests that are optimal up to constant or small polynomial factors in some regimes of n, d, γ and ρ. The randomized design/reconstruction algorithm in the ρ-sized test scenario is universal - independent of the value of d, as long as ρ ∈ o(n/d). We also investigate the

关键词： Recovery

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Twitter's glass ceiling: The effect of perceived gender on online visibility 10

Twitter's glass ceiling: The effect of perceived gender on o...

引用

10th International Conference on Web and Social Media, ICWSM 2016

作者： Nilizadeh, Shirin Groggel, Anne Lista, Peter Das, Srijita Ahn, Yong-Yeol Kapadia, Apu Rojas, Fabio Computer Science Department University of California Santa BarbaraCA United States Department of Sociology Indiana University Bloomington IN United States School of Informatics and Computing Indiana University Bloomington IN United States

ISBN: (纸本)9781577357582

Social media is a new public sphere where people can, in principle, communicate with each other regardless of their status. However, social categories like gender may still bias online communication, replicating offline disparities. Examining over 94,000 Twitter users, we investigate the association between perceived gender and measures of online visibility: how often Twitter users are followed, assigned to lists, and retweeted. Our analysis shows that users perceived as female experience a ?glass ceiling,' similar to the barrier women face in attaining higher positions in companies. For users in lower quartiles of visibility, being perceived as female is associated with more visibility;however, this tendency flips among the most visible users where being perceived as male is strongly associated with more visibility. Our results suggest that gender presented in social media profiles likely frame interactions as well as perpetuates old inequalities online. © Copyright 2016, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Visibility

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Anonymity networks and access to information during conflicts: Towards a distributed network organisation

Anonymity networks and access to information during conflict...

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International Conference on Cyber Conflict (ICCC)

作者： Paolo Palmieri Department of Computing and Informatics Bournemouth University Poole United Kingdom

Access to information is crucial during conflicts and other critical events such as population uprisings. An increasing number of social interactions happen in the cyberspace, while information exchanges at the infrastructural level (monitoring systems, sensor networks, etc.) are now also based on Internet and wireless links rather than ad hoc, isolated wired networks. However, the nature of the Internet allows powerful hostile actors to block, censor, or redirect communication to and from specific Internet services, through a number of available techniques. Anonymity networks such as Tor provide a way to circumvent traditional strategies for restricting access to online resources, and make communication harder to trace and identify. Tor, in particular, has been successfully used in past crises to evade censorship and Internet blockades (Egypt in 2011, and Iran in 2012). Anonymity networks can provide essential communication tools during conflicts, allowing information exchanges to be concealed from external observers, anonymised, and made resilient to imposed traffic controls and geographical restrictions. However, the design of networks such as Tor makes them vulnerable to large-scale denial of service attacks, as shown by the DDoS targeted at Tor hidden services in March 2015. In this paper, we analyse the structural weaknesses of Tor with regard to denial of service attacks, and propose a number of modifications to the structure of the Tor network aimed at improving its resilience to a large coordinated offensive run by a hostile actor in a conflict scenario. In particular, we introduce novel mechanisms that allow relay information to be propagated in a distributed and peer-to-peer manner. This eliminates the need for directory services, and allows the deployment of Tor-like networks in hostile environments, where centralised control is impossible. The proposed improvements concern the network organisation, but preserve the underlying onion routing mechanism tha

关键词： Relays Peer-to-peer computing Routing Wireless sensor networks Internet Computer crime Monitoring

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MULTIVARIATE CLUSTER PROFILING OF AMYLOID BETA, TAU, NEURODEGENERATION AND VASCULAR (ATNV) BIOMARKERS IN THE ADNI COHORT: IMPLICATIONS FOR COGNITION, –OMICS AND CLINICAL TRIALS

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Alzheimer's & Dementia 2018年第7期14卷 P1475-P1475页

作者： Andrew J. Saykin Shannon L. Risacher Kwangsik Nho Jingwen Yan Liana G. Apostolova Rima F. Kaddurah-Daouk Sujuan Gao Department of Radiology and Imaging Sciences Indiana University School of Medicine Indianapolis IN USA Indiana Alzheimer Disease Center Indianapolis IN USA Indiana University School of Medicine Indianapolis IN USA Indiana University School of Informatics and Computing Indianapolis IN USA Department of Medicine Duke University Durham NC USA

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Bayesian spatial binary regression for label fusion in structural neuroimaging

arXiv

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arXiv 2017年

作者： Brown, D. Andrew McMahan, Christopher S. Shinohara, Russell T. Linn, Kristin A. School Of Mathematical And Statistical Sciences Clemson University ClemsonSC29634 United States Penn Statistics In Imaging And Visualization Center Department Of Biostatistics Epidemiology And Informatics Center For Biomedical Image Computing And Analytics Department Of Radiology Perelman School Of Medicine University Of Pennsylvania PhiladelphiaPA19104 United States

Alzheimer's disease is a neurodegenerative condition that accelerates cognitive decline relative to normal aging. It is of critical scientific importance to gain a better understanding of early disease mechanisms in the brain to facilitate effective, targeted therapies. The volume of the hippocampus is often used in diagnosis and monitoring of the disease. Measuring this volume via neuroimaging is difficult since each hippocampus must either be manually identified or automatically delineated, a task referred to as segmentation. Automatic hippocampal segmentation often involves mapping a previously manually segmented image to a new brain image and propagating the labels to obtain an estimate of where each hippocampus is located in the new image. A more recent approach to this problem is to propagate labels from multiple manually segmented atlases and combine the results using a process known as label fusion. To date, most label fusion algorithms employ voting procedures with voting weights assigned directly or estimated via optimization. We propose using a fully Bayesian spatial regression model for label fusion that facilitates direct incorporation of covariate information while making accessible the entire posterior distribution. Our results suggest that incorporating tissue classification (e.g, gray matter) into the label fusion procedure can greatly improve segmentation when relatively homogeneous, healthy brains are used as atlases for diseased brains. The fully Bayesian approach also produces meaningful uncertainty measures about hippocampal volumes, information which can be leveraged to detect significant, scientifically meaningful differences between healthy and diseased populations, improving the potential for early detection and tracking of the disease. © 2017, CC BY.

关键词： Neurodegenerative diseases

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