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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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An AlN-based piezoelectric micro-machined ultrasonic transducer (pMUT) array

An AlN-based piezoelectric micro-machined ultrasonic transdu...

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IEEE Conference on Nanotechnology

作者： Qifeng Zhu Tao Chen Huicong Liu Lining Sun Tao Wang Chengkuo Lee Xianhao Le Jin Xie Jiangsu Provincial Key Labratory of Advanced Robotics Soochow University Suzhou China Department of Electrical and Computer Engineering National University of Singapore Singapore State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou China

The development of wireless energy transfer is critical to the promotion of implantable medical devices (IMDs). In this paper, an aluminum nitride (AlN) based piezoelectric micromachined ultrasonic transducer (pMUT) array is designed, fabricated and characterized, which can be a potential power supply for IMDs. The pMUT array is ideally suitable for integration with wireless-powered system since it is fabricated from miniaturized AlN membrane array of 4×4 units. Both the simulation and experiment are conducted to characterize the pMUT device. The transmitting sensitivity of the fabricated pMUT array is measured as 83 nm/V at a resonant frequency of 527 kHz.

关键词： Aluminum nitride III-V semiconductor materials Resonant frequency Sensitivity Ultrasonic transducers Acoustics Cavity resonators

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An analysis of sampling effect on bilateral teleoperation system transparency 34

An analysis of sampling effect on bilateral teleoperation sy...

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34th Chinese Control Conference, CCC 2015

作者： Ting, Yang Fu, Yi Li Tavakoi, Mahdi State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin Heilongjiang China Department of Electrical and Computer Engineering University of Alberta EdmontonAB Canada

ISBN: (纸本)9789881563897

The performances of continuous-time controlled and discrete-time controlled bilateral teleoperation systems are mathematically and experimentally studied and compared. The results show that under stability conditions, continuous-time controlled teleoperation systems have hybrid matrix parameters that are closer to their ideal values than their discrete-time controlled counterparts. This means better force tracking and position tracking performance under continuous-time control, which can lead to better task performance. © 2015 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Bilateral teleoperation continuous-time control discrete-time control hybrid parameters system performance

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Rewinding Strategy Aided by FEA as a Solution to Increase Efficiency of Industrial Motors

Rewinding Strategy Aided by FEA as a Solution to Increase Ef...

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International Conference on electrical Machines

作者： V. P. B. Aguiar R. S. T. Pontes T. R. Fernandes Neto F. J. T. E. Ferreira Motor Driven Systems Laboratory Department of Electrical Engineering Federal University of Ceará Fortaleza CE 60440554 Brazil Institute of Systems and Robotics Department of Electrical and Computer Engineering University of Coimbra Coimbra Portugal

ISBN: (纸本)9781509025398

This paper presents a proper model and methodology to improve the efficiency class of a squirrel-cage induction motor during rewinding. The modeling approach is based on the finite element model, i.e. two-dimensional model coupled with the rotor equivalent circuit (first stage) and the stator equivalent circuit (second stage). Results obtained with finite element analysis are compared with those obtained with analytical calculations. It is demonstrated that, during rewinding, if an improved winding configuration is used, efficiency gains can be obtained, allowing to improve the efficiency class of the motor, from IE2 to IE3, respecting the specified limits of NEMA & IEC performance indicators, namely, breakdown torque, locked-rotor torque, and locked-rotor current. In 79% of the simulated cases the efficiency gain allowed the studied motor to reach the IE3 class.

关键词： Finite element analysis Equivalent circuits IEEE standards IEC standards ANSI standards Stator Induction motors Electromagnetic modeling Frequency-domain analysis

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Optimal search strategies for pollutant source localization

Optimal search strategies for pollutant source localization

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Behzad Bayat Naveena Crasta Howard Li Auke Ijspeert BioRobotics Laboratory Ecole Polytechnique Federale de Lausanne (EPFL) Switzerland Institute for Systems and Robotics (ISR) Instituto Superior Tecnico (IST) University of Lisbon Portugal COBRA Department of Electrical and Computer Engineering University of New Brunswick Fredericton E3B 5A3 Canada

ISBN: (纸本)9781509037636

This paper is aimed at developing optimal motion planning for a single autonomous surface vehicle (ASV) equipped with an on-board pollutant sensor that will maximize the sensor-related information available for source seeking. The ASV uses a nonlinear diffusion model of the pollutant source to estimate the intensity/level of the pollution at the present ASV location. The rate of detection of particles depends on the relative distance between the ASV and the source. First, we use a probabilistic map of the source location built through the sensor information for a dynamic motion planning of source seeking based on an entropy reduction formulation, where an appropriately defined Fisher information matrix (FIM) is used for entropy reduction or information gain. We derive the FIM for the set-up and investigate optimal trajectories. Next, we present an online nonlinear Monte Carlo algorithm that uses the obtained sensor information about pollutant at different vehicle locations to update a probabilistic uncertainty map of pollutant source location. As the mission unfolds the ASV motion is computed by considering a moving-horizon interval of decision, which will allow for the inclusion of new information available for optimal motion planning. The proposed motion planning approach is extended to take into account external disturbances and it is able to minimize the uncertainty in the pollutant source. Finally, we provide two case studies to demonstrate efficacy of the proposed motion planning algorithm.

关键词： Position measurement Pollution measurement Uncertainty Planning Probabilistic logic Robot sensing systems Pollution

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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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An Analysis of Sampling Effect on Bilateral Teleoperation System Transparency

An Analysis of Sampling Effect on Bilateral Teleoperation Sy...

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第三十四届中国控制会议

作者： Ting YANG Yi Li FU Mahdi TAVAKOI State Key Laboratory of Robotics and Systems Harbin Institute of Technology Department of Electrical and Computer Engineering University of Alberta

ISBN: (纸本)9781467374439

关键词： Bilateral teleoperation,hybrid parameters,discrete-time control,continuous-time control,system performance

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FPAA-based Control of Bilateral Teleoperation systems

FPAA-based Control of Bilateral Teleoperation Systems

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第三十四届中国控制会议

作者： Ting YANG Yi Li FU Mahdi TAVAKOI State Key Laboratory of Robotics and Systems Harbin Institute of Technology Department of Electrical and Computer Engineering University of Alberta

ISBN: (纸本)9781467374439

Discretizing the continuous-time controller of a master-slave teleoperation system can simplify control implementation. However, in teleoperation systems, discrete-time control can cause a performance degradation compared to continuous-time control. In digitally controlled bilateral teleoperation systems, there exist stability-imposed bounds on the gains of the discrete-time controller and the sampling period, and a trade-off between the two. This means that given a sampling period, it is impossible for the discretized controller to have gains above a threshold, which may well be necessary for successful performance of teleoperated tasks requiring highly accurate master-slave position tracking. In a teleoperation system with analog controller, however, stability does not impose any upper bound on the control gains, thus facilitating the performance of tasks that do require highly accurate master-slave position tracking. Inspired by this advantage of analog control, in this paper we develop a Field Programmable Analog Arrays(FPAA) based controller for bilateral teleoperation, which can achieve higher control gain than its discrete-time counterpart. We present the results of a user study measuring the human performance for a task involving flipping a stiff switch through a teleoperation system. We experimentally show that large sampling periods, necessitating low control gains for maintaining stability, lead to unacceptable task performance. We then show that humans can successfully perform the same task with the FPAA-based controller for the teleoperation system.

关键词： Bilateral teleoperation,stability,discrete-time control,FPAA-based control,task performance

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[email protected] : Analysis and results of evolving competitions for domestic and service robots

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Artificial Intelligence 2015年 229卷 258-281页

作者： Luca Iocchi Dirk Holz Javier Ruiz-del-Solar Komei Sugiura Tijn van der Zant Department of Computer Control and Management Engineering Sapienza University of Rome Italy Autonomous Intelligent Systems Group University of Bonn Germany Department of Electrical Engineering & Advanced Mining Technology Center Universidad de Chile Chile Information Services Platform Laboratory National Institute of Information and Communications Technology Japan Cognitive Robotics Laboratory University of Groningen The Netherlands

Scientific competitions are becoming more common in many research areas of artificial intelligence and robotics, since they provide a shared testbed for comparing different solutions and enable the exchange of research results. Moreover, they are interesting for general audiences and industries. Currently, many major research areas in artificial intelligence and robotics are organizing multiple-year competitions that are typically associated with scientific conferences. One important aspect of such competitions is that they are organized for many years. This introduces a temporal evolution that is interesting to analyze. However, the problem of evaluating a competition over many years remains unaddressed. We believe that this issue is critical to properly fuel changes over the years and measure the results of these decisions. Therefore, this article focuses on the analysis and the results of evolving competitions. In this article, we present the [email protected] competition, which is the largest worldwide competition for domestic service robots, and evaluate its progress over the past seven years. We show how the definition of a proper scoring system allows for desired functionalities to be related to tasks and how the resulting analysis fuels subsequent changes to achieve general and robust solutions implemented by the teams. Our results show not only the steadily increasing complexity of the tasks that [email protected] robots can solve but also the increased performance for all of the functionalities addressed in the competition. We believe that the methodology used in [email protected] for evaluating competition advances and for stimulating changes can be applied and extended to other robotic competitions as well as to multi-year research projects involving Artificial Intelligence and robotics.

关键词： Robotic competitions Artificial intelligence and robotics Benchmarking

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Robotic Software System for the Disaster Circumstances: System of Team KAIST in the DARPA robotics Challenge Finals

Robotic Software System for the Disaster Circumstances: Syst...

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IEEE-RAS International Conference on Humanoid Robots

作者： Jeongsoo Lim Inwook Shim Okkee Sim Hyunmin Joe Inhyeok Kim Jungho Lee Jun-Ho Oh Humanoid Research Center School of Mechanical Aerospace & Systems Engineering Department of Mechanical Engineering Korea Advanced Institute of Science and Technology Robotics and Computer Vision Laboratory Department of Electrical Engineering College of Information Science and Technology Korea Advanced Institute of Science and Technology Rainbow Co.

ISBN: (纸本)9781479968862

We developed a software system for operating the humanoid robot DRC-HUBO+ in disaster circumstances that the US Defense Advanced Research Projects Agency suggested. This system was developed under the consideration of the stability of whole system, the systemic software environment for multiple developers, and the recovery routine when the system encounters a seriously abnormal situation. With these design goals, we devised our strategy for three domains: system, vision, and communication. Following the strategy we made two software frameworks (PODO and VPC) and one logical flow of data for remote process management. With this software system, we conducted all Tasks in the DARPA robotics Challenge Finals, and we won the competition.

关键词： Software systems DARPA design target robotics Disasters Religious Missions flow datas

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