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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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A study on tracking peformance of the pneumatic system with enhanced NPID controller

A study on tracking peformance of the pneumatic system with ...

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Asian control Conference

作者： Sy Najib Sy Salim Aliza Che Amran A. A. M. Faudzi Z. H. Ismail M. F. Rahmat N. H. Sunar Shamsul Anuar Shamsudin Department of Control Instrumentation and Automation Faculty of Electrical Engineering Universiti Teknikal Malaysia Melaka Department of Control Universiti Teknikal Malaysia Melaka Department of Control and Mechatronic Engineering Universiti Teknologi Malaysia Centre for Artificial Intelligence & Robotics (CAIRO) Universiti Teknologi Malaysia Kuala Lumpur Malaysia Faculty of Mechanical Engineering Universiti Teknikal Malaysia Melaka

An investigation on the performance of enhanced Nonlinear Proportional Integral Derivative (ENPID) controller is presented in this paper. The study is focused on the potential of the controller to perform well in tracking set point of pneumatic actuator system. Two control strategies of the ENPID are considered in this paper, namely Multi-rate NPID (MN-PID) and Self-regulation NPID (SN-PID). These control strategies are tested against NPID and conventional PID controller. Also, the dead-zone compensation (DZC) is applied to the system to overcome the dead-band of the valve. Feed forward path is also included to improve the tracking performance. Two different input signals i.e. sinusoidal and S-curve waveforms are used to evaluate the performance of the techniques. To further examine the controller performance, the frequency and amplitude of the sinusoidal test signal are varied. The effectiveness of the proposed controllers is verified through simulation and experimental studies.

关键词： Pneumatic actuators Valves Mathematical model Trajectory Pistons Fuzzy logic

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Dynamic control of a Walking Robot Using the Versatile Intelligent Portable Robot Platform

Dynamic Control of a Walking Robot Using the Versatile Intel...

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International Conference on control Systems and Computer Science (CSCS)

作者： Victor Vladareanu Corina Boscoianu Radu I. Munteanu Hongnian Yu Luige Vladareanu Robotics and Mechatronics Department Romanian Academy Institute of Solid Mechanics Bucharest ROMANIA Department of Automatic Control and Systems Engineering Faculty of Electrical Engineering Technical University of Cluj-Napoca Napoca ROMANIA School of Design Engineering and Computing Bournemouth University Poole UK Bournemouth UK

This paper studies the walking robot hybrid dynamic control in real time in order to increase movement stability of walking robots on flat terrain, with obstacles or uneven ground, at constant or variable walking speed and variable load. The motion trajectory positions of the robot leg end-effect or and joints, reaction forces and the walking robot dynamics are analyzed and the virtual projection method is adopted using the Versatile Intelligent Portable Robot Platform VIPRO. The obtained results lead to higher performance in relation to the walking robots movement possibilities, the real-time robot balance control, gait control and predictable motion control, providing increased mobility and stability, and also the development of new technological capabilities of the control systems.

关键词： Legged locomotion Stability analysis control systems Real-time systems Robot kinematics Dynamics

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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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Two chambers soft actuator realizing robotic gymnotiform swimmers fin

Two chambers soft actuator realizing robotic gymnotiform swi...

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2014 IEEE International Conference on robotics and Biomimetics, IEEE ROBIO 2014

作者： Razif, Muhammad Rusydi Muhammad Faudzi, Ahmad Athif Mohd Bavandi, Mahrokh Nordin, Najaa Aimi Mohd Natarajan, Elango Yaakob, Omar Department of Mechatronics and Robotics Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia Skudai81310 Malaysia Department of Control and Mechatronic Engineering Faculty of Electrical Engineering Universiti Teknologi Malaysia Skudai81310 Malaysia Marine Technology Center Universiti Teknologi Malaysia Skudai81310 Malaysia

ISBN: (纸本)9781479973965

This paper shows a study on two chambers soft actuator development and its application to an artificial soft actuator fin. Simulations of two chambers actuator are conducted using finite element method software and the bending angles produced are computed. Eleven designs are proposed and compared which differ in separating wall thickness, actuator thickness, fiber location, fiber materials, and rubber materials to analyze the optimal bending angle produced by the actuator. Two actuators are then fabricated and embedded at the ends of soft actuator fin to produce a traveling wave along the soft actuator fin. Soft actuator fin propels like gymnotiform swimmers and shows good linear motion. © 2014 IEEE.

关键词： Actuators

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Vision-Based Kinematic Calibration of Spherical Robots

Vision-Based Kinematic Calibration of Spherical Robots

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RSI/ISM International Conference on robotics and Mechatronics

作者： Pedram Agand Hamid D. Taghirad Amir Molaee Advanced Robotics and Automation System (ARAS) Industrial Control Center of Excellence (ICEE) Department of Systems and Control Faculty of Electrical Engineering K. N. Toosi University of Technology Iran

ISBN: (纸本)9781467372350

In this article, a method to obtain spatial coordinate of spherical robot's moving platform using a single camera is proposed, and experimentally verified. The proposed method is an accurate, flexible and low-cost tool for the kinematic calibration of spherical-workspace mechanisms to achieve the desired accuracy in position. The sensitivity and efficiency of the provided method is thus evaluated. Furthermore, optimization of camera location is outlined subject to the prescribed cost functions. Finally, experimental analysis of the proposed calibration method on ARAS Eye surgery Robot (DIAMOND) is presented;In which the accuracy is obtained from three to six times better than the previous calibration.

关键词： Kinematic Calibration Vision-Base Positioning Eye Surgery Robot Spherical Workspace

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Development of a Hybrid-driven Autonomous Underwater Glider with a Biologically Inspired Motion control System

Development of a Hybrid-driven Autonomous Underwater Glider ...

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Asian control Conference

作者： Khalid Isa M. R. Arshad Embedded Computing System Research Group (EmbCos) Faculty of Electrical and Electronic Engineering Universiti Tun Hussein Onn Malaysia (UTHM) Underwater Control and Robotics Group (UCRG) School of Electrical and Electronic Engineering Engineering Campus Universiti Sains Malaysia (USM)

ISBN: (纸本)9781479978632

This paper presents prototype development of a hybrid-driven autonomous underwater glider with a biologically inspired motion control system. The hybrid-driven glider with an independently controllable wings and a rudder was developed to overcome the drawback of a typical buoyancy-driven underwater glider in terms of speed and maneuverability. However, it is difficult to control the glider due to the high nonlinear and time-varying dynamic behavior of the glider;uncertainties in hydrodynamics coefficients;and disturbances by water currents. Thus, a robust and reliable bio-inspired controller algorithm has been designed. The controller algorithm has been designed to mimic a human innate control mechanism, which is known as homeostatic controller. The performance of the homeostatic controller of the hybrid-driven glider has been analyzed via simulation and experimental. From the simulation result, our homeostatic controller achieves better performance compared to the LQR, MPC, NN and neuroendocrine controller approaches. Furthermore, validation analysis of the homeostatic controller performance between the simulation and experimental results have shown very satisfactory performance.

关键词： Hybrid-driven underwater glider Homeostatic controller Motion control Homeostasis

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An approach to determination of simple circular waits in reconfigurable multi-vehicle systems

An approach to determination of simple circular waits in rec...

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IEEE Conference on control Technology and Applications (CCTA)

作者： Tamara Petrovic Stjepan Bogdan Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems (LARICS)

ISBN: (纸本)9781479974108

Resource allocation systems are used for modeling and control of flexible manufacturing systems, multi-vehicle systems, traffic networks, etc. Methods for control of these systems are often based on the identification of a special structural property, simple circular wait of resources, and interrelations between simple circular waits. In this paper we study reconfigurable resource allocation systems, which require that control algorithm is modified online and, therefore, has low running time. In this paper we propose dynamical algorithms for determination of simple circular waits in reconfigurable systems, which are based on Johnson's algorithm, and aim at identifying only changes in the set of simple circular waits. Running time of the proposed algorithms is lower than running time of standard static methods. Algorithms are tested for a family of multi-vehicle systems and results confirm the advantages of using the dynamic algorithms.

关键词： Vehicles Heuristic algorithms Resource management Motion segmentation Algorithm design and analysis Complexity theory System recovery

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Path assignment and resource allocation control in reconfigurable multi-vehicle system

Path assignment and resource allocation control in reconfigu...

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IEEE Conference on control Technology and Applications (CCTA)

作者： Tamara Petrovic Faculty of Electrical Engineering and Computing Laboratory for Robotics and Intelligent Control Systems (LARICS)

ISBN: (纸本)9781479974108

In this paper we study control of reconfigurable multi-vehicle system. Our method builds upon an existing deadlock-free resource allocation control method that is based on the identification of higher-level deadlocks. We identify a smaller set of cyclic circular waits to be controlled, and provide an algorithm for determination of such cyclic circular waits. Furthermore, we propose a path assignment algorithm that aims at lowering the structural complexity of the corresponding resource allocation system, while taking into account path length. Methods are tested in a simulation environment and results show their efficiency.

关键词： System recovery Vehicles Resource management Motion segmentation control systems Heuristic algorithms Superluminescent diodes

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SMC with Linear Dynamic Compensator Design: Performance Margins Approach

SMC with Linear Dynamic Compensator Design: Performance Marg...

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IEEE Annual Conference on Decision and control

作者： Antonio Rosales Leonid Fridman Yuri Shtessel Deparment of Control and Robotics Faculty of Engineering National Autonomus University of Mexico 4510 Mexico City Mexico Electrical and Computer Engineering Dept. The University of Alabama in Huntsville Huntsville AL 35899 USA

ISBN: (纸本)9781467360890

In this work, the performance of the real sliding mode is characterized with the notion of performance margins under the assumption that the real sliding motion presents a limit cycle with acceptable amplitude and acceptable frequency. The performance of sliding mode controllers, in real sliding motion, is improved by means of the addition of linear compensators in cascade connection with the plant. The applied compensators are phase lead controllers which modify the frequency response of the plant in order to meet the required performance margins adding robustness to the system. Bode diagram interpretation of performance margins is presented for the first time allowing the utilization of SMC combined with the classical methodology of linear compensator design where it is possible shape the Bode diagram in order to obtain desired values of performance margins. Examples supporting the proposed idea are presented.

关键词： Bode diagrams frequency response margins limit cycles Cascade connections design performance COMPENSATORS Sliding mode

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