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research Square 2021年

作者： Yang, Hong Jin, Zhen Complex System Research Center Shanxi University Shanxi Taiyuan030006 China Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention Shanxi University Shanxi Taiyuan030006 China

Influenza is an infectious disease with obvious periodic changes over time. It is of great practical significance to explore the non-environment-related factors that cause this regularity for influenza control and individual protection. In this paper, based on the randomness of population number and the heterogeneity of population contact, we have established a stochastic infectious disease model about influenza based on the degree of the network, and obtained the power spectral density function by using the van Kampen expansion method of the master equation. The relevant parameters are obtained by fitting the influenza data of sentinel hospitals. The results of the numerical analysis show that: (1) for the infected, the infection period of patients who go to the sentinel hospitals is particularly different from the others who do not;(2) for all the infected, there is an obvious nonlinear relationship between their infection period and the visiting rate of the influenza sentinel hospitals, the infection rate and the degree. Among them, only the infection period of patients who do not go to the sentinel hospitals decreased monotonously with the infection rate (increased monotonously with the visiting rate), while the rest had a nonmonotonic relationship. © 2021, CC BY.

关键词： Stochastic models

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Parameter adaptive terminal sliding mode control of flexible coupling air-breathing hypersonic vehicle

Parameter adaptive terminal sliding mode control of flexible...

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AIAA Scitech Forum, 2020

作者： Jin, Hengxian Chen, Haibing Lin, Wei Xu, Cheng School of Energy And Power Engineering Beihang University Beijing100191 China Airworthiness Technologies Research Center School of Transportation Science and Engineering Beihang University Beijing100191 China School of Transportation Science and Engineering Beihang University Beijing100191 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

Flexible air-breathing hypersonic vehicles have very wide range of flight and show significant and complex aerodynamic, scramjet propulsion system, flight dynamic and elastic coupling characteristics, which usually are highly nonlinear. These result in huge uncertainties, parameter perturbation and internal disturbance, which can no longer be ignored, and therefore, extreme difficulties for flight control design. A unique parameter adaptive nonsingular terminal sliding mode method is proposed for longitudinal control law design of a flexible coupling air-breathing hypersonic vehicle. Other than conventional adaptive terminal sliding mode control, this method uses adaptive reaching law gain instead of additional adaptive compensation term to handle the uncertainty to improve robustness. The stability of the close loop system is proved via a Lyapunov way. The longitudinal tracking control law for velocity and angle of attack is designed based on a rigid dynamic model of a flexible air-breathing hypersonic vehicle. A strong coupling model of this vehicle, considering aerodynamic-scramjet engine-flight dynamic-elastic couplings, is established as the verification platform of control law designed. The remarkable differences of flight dynamics characteristics between this strong coupling model and the rigid body model can be seen, which mean the controller needs to endure very great uncertainty, unmodeled dynamics and other internal disturbance. Simulation based on the coupling model is carried on and results demonstrate that the control law designed has good performance and acceptable robustness. © 2020, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Hypersonic vehicles

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Nonpharmaceutical interventions contribute to the control of COVID-19 in China based on a pairwise model

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Infectious Disease Modelling 2021年第1期6卷 643-663页

作者： Xiao-Feng Luo Shanshan Feng Junyuan Yang Xiao-Long Peng Xiaochun Cao Juping Zhang Meiping Yao Huaiping Zhu Michael Y.Li Hao Wang Zhen Jin Department of Mathematics North University of ChinaTaiyuanShanxi030051China Complex System Research Center Shanxi UniversityTaiyuan030006ShanxiChina Shanxi Key Laboratory of Mathematical Techniques and Big Data Analysis on Disease Control and Prevention Shanxi UniversityTaiyuan030006ShanxiChina School of Mathematical Sciences Shanxi UniversityTaiyuan030006ShanxiPR China Department of Mathematics and Statistics York UniversityTorontoONM3J 1P3Canada Department of Mathematics and Statistics Sciences University of AlbertaEdmontonAlbertaT6G 2G1Canada

Nonpharmaceutical interventions(NPIs),particularly contact tracing isolation and household quarantine,play a vital role in effectively bringing the Coronavirus Disease 2019(COVID-19)under control in *** pairwise model,has an inherent advantage in characterizing those two NPIs than the classical well-mixed ***,in this paper,we devised a pairwise epidemic model with NPIs to analyze COVID-19 outbreak in China by using confirmed cases during February 3rde22nd,*** explicitly incorporating contact tracing isolation and family clusters caused by household quarantine,our model provided a good fit to the trajectory of COVID-19 *** calculated the reproduction number R=1.345(95%CI:1.230-1.460)for Hubei province and R=1.217(95%CI:1.207-1.227)for China(except Hubei).We also estimated the peak time of infections,the epidemic duration and the final size,which are basically consistent with real *** indicated by simulation that the traced high-risk contacts from incubated to susceptible decrease under NPIs,regardless of infected *** sensitivity analysis showed that reducing the exposure of the susceptible and increasing the clustering coefficient bolster COVID-19 *** the enforcement of household quarantine,the reproduction number R and the epidemic prevalence declined ***,we obtained the resumption time of work and production in China(except Hubei)on 10th March and in Hubei at the end of April 2020,respectively,which is broadly in line with the actual *** results may provide some potential lessons from China on the control of COVID-19 for other parts of the world.

关键词： COVID-19 Pairwise epidemic model Household quarantine Clustering coefficient High-risk contacts

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Emissions reduction potential and feasibility of vehicle-to-grid for Beijing’s future electric vehicles

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Cell Reports Physical Science 2025年

作者： Jiaxin Xu Jiahui Chen Hongyi Wei Yinan Zhao Bowen Tian Yifan Wen Haiyang Jiang Ning Zhang Shaojun Zhang Ye Wu School of Environment Tsinghua University Beijing 100084 China Center for Sustainable Systems School for Environment and Sustainability University of Michigan Ann Arbor MI 48109 USA School of Electrical and Power Engineering Power System Research Institute Tsinghua University Beijing 100084 China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084 China Beijing Laboratory of Environmental Frontier Technologies School of Environment Tsinghua University Beijing 100084 China State Key Laboratory of Regional Environment and Sustainability Tsinghua University Beijing 100084 China

Electric vehicles (EVs) offer significant potential to reduce greenhouse gas (GHG) emissions from road transport. However, nighttime charging increases peak demand and thermal power reliance. This study evaluates vehicle-to-grid (V2G) as a solution by integrating GPS-based EV travel data with hourly grid modeling for 2 million EVs in Beijing. Results show V2G boosts renewable energy use in charging to 66%, up from under 4% in uncoordinated charging. V2G cuts vehicle uncoordinated charging emissions by 20.6% and reduces the grid’s GHG footprint by replacing thermal power with discharging electricity. Commuter vehicles and the summer months offer the highest V2G emissions reduction potential. The study finds battery degradation manageable and highlights synergies between V2G, renewable capacity expansion, and economic incentives, while emphasizing the need for robust infrastructure and local grid networks to support large-scale EV adoption. This approach therefore offers a promising pathway to accelerate sustainable energy solutions amid increasing vehicle electrification and renewable integration.

关键词： electric vehicles vehicle to grid V2G GHG emissions travel pattern grid optimization

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Blockchain-based Social Manufacturing for Customization Production

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IFAC-PapersOnLine 2020年第5期53卷 53-58页

作者： Xiuqin Shang Xi Chen Lulu Niu Gang Xiong Zhen Shen Xisong Dong Zhengchao Shen Chao Liu Bangwen Xi the Research Center of Precision Sensing and Control the state key laboratory for management and control of complex systems & Beijing engineering research center of intelligent systems and technology institute of automation Chinese Academy of Sciences Beijing 100190 China Beijing University of Posts and Telecommunications Beijing 100876 China Alstom Beizhong Power (Beijing) Co. Ltd. Beijing 100040 China the System Integration Electronics (Hangzhou)Co. LTD No. 58 No. 11 Road Foxconn Qiantang Tech-Industrial Area HETZ Hangzhou 310018 China

This paper proposes the social manufacturing based on Blockchain, which realizes precise and efficient customization through smart contract and distributed accounting. It is a new manufacturing mode of service-oriented, distributed and collaborative customization. This paper proposes the definition of SM based on Blockchain. In the process of using to Blockchain, it can form a strong trust relationship, so that multiple nodes / roles in SM can save the complete copy of the whole database, rather than a centralized permission / role. Secondly, the Blockchain-based SM system is developed for customized manufacturing. Finally, its application case and the optimization results are given. In SM, it is the key that how to transform customized manufacturing actions into socialized actions of manufacturing resources through internet communities and interconnect Socialized Manufacturing Resources (SMRs) in upstream and downstream. In this paper, the smart contract relationship is established based on Blockchain between SMRs to build credit mechanism in SM, Which can ensure the effective circulation and association of SMRs.

关键词： Social Manufacturing Blockchain Optimization SM Resources

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Sources of atmospheric glyoxal and methylglyoxal in Beijing and its impact on wintertime secondary organic aerosol formation

Sources of atmospheric glyoxal and methylglyoxal in Beijing ...

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第二十四届大气污染防治技术研讨会

作者： Xionghui Qiu Shuxiao Wang Qi Ying Lei Duan Jia Xing Jingyuan Cao Di Wu Xiaoxiao Li Chengzhi Xing Xiao Yan Cheng Liu Jiming Hao MOE Key Laboratory of Resources and Environmental System Optimization College of Environmental Science and Engineering North China Electric Power University State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Zachry Department of Civil Engineering Texas A&M University College Station School of Earth and Space Sciences University of Science and Technology of China National Engineering Research Center of Urban Environmental Pollution Control Beijing Municipal Research Institute of Environmental Protection Department of Precision Machinery and Precision Instrumentation University of Science and Technology of China

Atmospheric glyoxal(GLY) and methylglyoxal(MGLY) are key precursors of secondary organic aerosol(SOA). However, anthropogenic emissions of GLY and MGLY and their contribution to surface GLY and MGLY concentrations, as well as the secondary organic aerosol(SOA) formation, are not well quantified. By developing an emission inventory of anthropogenic GLY and MGLY and improving Community Multiscale Air Quality Model(CMAQ) with SOA formation from irreversible surface uptake of GLY and MGLY, as well as a precursor-origin resolved technique, we quantified the source contributions of GLY and MGLY and their impact on wintertime SOA formation in Beijing, China. The total emissions of GLY and MGLY in Beijing in 2017 are 1.1×10～4 kmol and 7.0×10～3 kmol, respectively. Anthropogenic primary emissions are found to be the dominant contributor to GLY and MGLY concentrations(～74% for GLY and ～63% for MGLY). Anthropogenic primary emissions of GLY and MGLY contributes to 30% of GLY/MGLY SOA daily average concentration and accounts for up to 45% of nighttime GLY/MGLY SOA. The study suggests that the anthropogenic GLY and MGLY emissions, mainly from gasoline vehicles and cooking, are important for SOA formation and shall be strictly controlled in Chinese megacities.

关键词： SOA Sources of atmospheric glyoxal and methylglyoxal in Beijing and its impact on wintertime secondary organic aerosol formation

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Comparation of Aroma-Active Compounds in Fresh Commercial Infant Formula and the Change during Ambient Storage

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Journal of Future Foods 2025年

作者： Lirong Xu Ailing Tian Jiayi Su Meifan Pan Riqing Liu Peipei Gao Beilei Pang Zitong Liu Lijiao Fan Huaixia Zhang Yali Wang Lei Du Lili Zheng Yingchun Zhao Xiaoxiao Feng Jing Lv Department of Nutrition The Affiliated Hospital of Qingdao University Qingdao China Institute of Nutrition and Health Qingdao University 266071 Qingdao China Department of Gastrointestinal Surgery The Affiliated Hospital of Qingdao University Jiangsu Road 16# Qingdao Shandong 266400 People's Republic of China Department of Health Education and Management and the Ministry of Education Key Lab of Hazard Assessment and Control in Special Operational Environment School of Public Health Fourth Military Medical University Xi'an China. Department of surgery The Affiliated Hospital of Qingdao University Qingdao China National Engineering Research Centre for Intelligent Electrical Vehicle Power System (Qingdao) College of Mechanical & Electronic Engineering Qingdao University Qingdao 266071 China College of Chemical Engineering Qingdao University of Science and Technology Analysis and Testing Center Qingdao University of Science and Technology 266042 Qingdao China Department of Food Science & Technology School of Agriculture & Biology Shanghai Jiao Tong University Shanghai 200240 China

This study compared the aroma-active compounds in 14 brands of commercially infant formula and investigated their changes during ambient storage after opening for 2 months. A total of 29 major aroma-active compounds were detected in infant formula. From the PCA and heatmap analysis, a total of 14 brands of infant formula were classified into 3 groups, the second group contained JLB-Y, AY and FH-F, of which 2-furanmethanol and (E,E)-3,5-octadien-2-one were mainly compounds, the third group contained YL and JLB-L, the characteristic flavor compounds in this group were mainly hexanal, heptanal, etc. Aldehydes, as the main volatile substances, account for more than half of the total volatiles. Nearly half of the aldehydes showed more significant changes after storage, e.g. hexanal, octanal, (E)-2-octenal and 3-methylbutyraldehyde. The YL and YP-Q produced more saturated aldehydes after storage, the concentration of hexanal in YL-2m and YP-Q-2m was 2138.5 μg/kg and 2004.1μg/kg, respectively. The concentrations of heptanal, octanal, and nonanal also increased relatively significantly, which may lead to a distinct rancid flavor in YL and YP-Q. Besides, among the ketones, (E,E)-3,5-octadien-2-one showed the greatest change after storage, especially in JLB-L. According to sensory evaluation experiments, the milky flavor of infant formulas decreased and fatty, rancid, fishy and grassy flavors were found to have increased to different extents after storage. The current information gap on the concentration and evolution of volatile compounds in commercially available infant formula is filled by this study.

关键词： Infant formula Volatile compounds GC-MS Ambient Storage

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Author Correction: The power of genetic diversity in genome-wide association studies of lipids

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Nature 2023年第7965期618卷 E19-E20页

作者： Sarah E Graham Shoa L Clarke Kuan-Han H Wu Stavroula Kanoni Greg J M Zajac Shweta Ramdas Ida Surakka Ioanna Ntalla Sailaja Vedantam Thomas W Winkler Adam E Locke Eirini Marouli Mi Yeong Hwang Sohee Han Akira Narita Ananyo Choudhury Amy R Bentley Kenneth Ekoru Anurag Verma Bhavi Trivedi Hilary C Martin Karen A Hunt Qin Hui Derek Klarin Xiang Zhu Gudmar Thorleifsson Anna Helgadottir Daniel F Gudbjartsson Hilma Holm Isleifur Olafsson Masato Akiyama Saori Sakaue Chikashi Terao Masahiro Kanai Wei Zhou Ben M Brumpton Humaira Rasheed Sanni E Ruotsalainen Aki S Havulinna Yogasudha Veturi QiPing Feng Elisabeth A Rosenthal Todd Lingren Jennifer Allen Pacheco Sarah A Pendergrass Jeffrey Haessler Franco Giulianini Yuki Bradford Jason E Miller Archie Campbell Kuang Lin Iona Y Millwood George Hindy Asif Rasheed Jessica D Faul Wei Zhao David R Weir Constance Turman Hongyan Huang Mariaelisa Graff Anubha Mahajan Michael R Brown Weihua Zhang Ketian Yu Ellen M Schmidt Anita Pandit Stefan Gustafsson Xianyong Yin Jian'an Luan Jing-Hua Zhao Fumihiko Matsuda Hye-Mi Jang Kyungheon Yoon Carolina Medina-Gomez Achilleas Pitsillides Jouke Jan Hottenga Gonneke Willemsen Andrew R Wood Yingji Ji Zishan Gao Simon Haworth Ruth E Mitchell Jin Fang Chai Mette Aadahl Jie Yao Ani Manichaikul Helen R Warren Julia Ramirez Jette Bork-Jensen Line L Kårhus Anuj Goel Maria Sabater-Lleal Raymond Noordam Carlo Sidore Edoardo Fiorillo Aaron F McDaid Pedro Marques-Vidal Matthias Wielscher Stella Trompet Naveed Sattar Line T Møllehave Betina H Thuesen Matthias Munz Lingyao Zeng Jianfeng Huang Bin Yang Alaitz Poveda Azra Kurbasic Claudia Lamina Lukas Forer Markus Scholz Tessel E Galesloot Jonathan P Bradfield E Warwick Daw Joseph M Zmuda Jonathan S Mitchell Christian Fuchsberger Henry Christensen Jennifer A Brody Mary F Feitosa Mary K Wojczynski Michael Preuss Massimo Mangino Paraskevi Christofidou Niek Verweij Jan W Benjamins Jorgen Engmann Rachel L Kember Roderick C Slieker Ken Sin Lo Nuno R Zilhao Phuong Le Marcus E Kleber Graciela E Delgado Shaofeng Huo Dai Department of Internal Medicine Division of Cardiology University of Michigan Ann Arbor MI USA. VA Palo Alto Health Care System Palo Alto CA USA. Department of Medicine Division of Cardiovascular Medicine Stanford University School of Medicine Stanford CA USA. Department of Computational Medicine and Bioinformatics University of Michigan Ann Arbor MI USA. William Harvey Research Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Department of Biostatistics and Center for Statistics Genetics University of Michigan Ann Arbor MI USA. Department of Genetics Perelman School of Medicine University of Pennsylvania Philadelphia PA USA. Clinical Pharmacology William Harvey Research Institute Barts and The London School of Medicine and Dentistry Queen Mary University of London London UK. Endocrinology Boston Children's Hospital Boston MA USA. Medical and Population Genetics Broad Institute Cambridge MA USA. Department of Genetic Epidemiology University of Regensburg Regensburg Germany. McDonnell Genome Institute and Department of Medicine Washington University St Louis MO USA. Department of Precision Medicine Division of Genome Science National Institute of Health Cheongju-si South Korea. Tohoku Medical Megabank Organization Tohoku University Sendai Japan. Sydney Brenner Institute for Molecular Bioscience Faculty of Health Sciences University of the Witwatersrand Johannesburg South Africa. Center for Research on Genomics and Global Health National Human Genome Research Institute National Institutes of Health Bethesda MD USA. Blizard Institute Barts and the London School of Medicine and Dentistry Queen Mary University of London London UK. Wellcome Sanger Institute Hinxton UK. Department of Epidemiology Emory University Rollins School of Public Health Atlanta GA USA. Atlanta VA Health Care System Decatur GA USA. Malcolm Randall VA Medical Center Gainesville FL USA. Division of Vascular Sur

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PID parameters optimization research for hydro turbine governor by an improved fuzzy particle swarm optimization algorithm

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Open Electrical and Electronic Engineering Journal 2016年 10卷 101-117页

作者： Chen, Gonggui Yangwei, Du Yanyan, Guo Shanwai, Huang Lilan, Liu Key Laboratory of Industrial Wireless Network and Networked Control of Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Research Center on Complex Power System Analysis and Control Chongqing University of Posts and Telecommunications Chongqing400065 China The Department of Locomotive and Vehicle Engineering Wuhan Railway Vocational College of Technology Wuhan430205 China

Parameter optimization of water turbine regulating system (WTRS) is decisive in providing support for the power quality and stability analysis of power system. In this paper, an improved fuzzy particle swarm optimization (IFPSO) algorithm is proposed and used to solve the optimization problem for WTRS under frequency and load disturbances conditions. The novel algorithm which is based on the standard particle swarm optimization (PSO) algorithm can speed up the convergence speed and improve convergence precision with combination of the fuzzy control thought and the crossover thought in genetic algorithm (GA). The fuzzy control is employed to get better dynamics of balance between global and local search capabilities, and the crossover operator is introduced to enhance the diversity of particles. Two different types of WTRS systems are built and analyzed in the simulation experiments. Furthermore, the sum of regulating time and another number that is the integral of sum for absolute value of system error and the squared governor output signal is considered as the fitness function of this algorithm. The simulation experiments for parameter optimization problem of WTRS system are carried out to confirm the validity and superiority of the proposed IFPSO, as compared to standard PSO, Ziegler Nichols (ZN) algorithm and fuzzy PID algorithm in terms of parameter optimization accuracy and convergence speed. The simulation results reveal that IFPSO significantly improves the dynamic performance of system under all of the running conditions. © Gonggui et al.

关键词： Fuzzy control

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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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