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arXiv 2022年

作者： Li, Lei Wu, Fuping Wang, Sihan Luo, Xinzhe Martín-Isla, Carlos Zhai, Shuwei Zhang, Jianpeng Liu, Yanfei Zhang, Zhen Ankenbrand, Markus J. Jiang, Haochuan Zhang, Xiaoran Wang, Linhong Arega, Tewodros Weldebirhan Altunok, Elif Zhao, Zhou Li, Feiyan Ma, Jun Yang, Xiaoping Puybareau, Elodie Oksuz, Ilkay Bricq, Stephanie Li, Weisheng Punithakumar, Kumaradevan Tsaftaris, Sotirios A. Schreiber, Laura M. Yang, Mingjing Liu, Guocai Xia, Yong Wang, Guotai Escalera, Sergio Zhuang, Xiahai School of Data Science Fudan University Shanghai China School of Biomedical Engineering Shanghai Jiao Tong University Shanghai China Departament de Matemàtiques & Informàtica Universitat de Barcelona Barcelona Spain Computer Vision Center Universitat Autònoma de Barcelona Spain School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Science and Engineering Northwestern Polytechnical University Xi'An China College of Electrical and Information Engineering Hunan University Changsha China National Engineering Laboratory for Robot Visual Perception and Control Technology Changsha China College of Physics and Information Engineering Fuzhou University Fuzhou China Comprehensive Heart Failure Center Wuerzburg University Hospitals Wuerzburg Germany School of Engineering University of Edinburgh Edinburgh United Kingdom School of Robotics Xi'an Jiaotong-Liverpool University Suzhou China Department of Electrical and Computer Engineering University of California Los Angeles United States Department of Radiology and Diagnostic Imaging University of Alberta Edmonton Canada Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecomm-Unications Chongqing China ImViA Laboratory Université Bourgogne Franche-Comté Dijon France Computer Engineering Department Istanbul Technical University Istanbul Turkey Le Kremlin-Bicêtre France Department of Mathematics Nanjing University of Science and Technology Nanjing China Department of Mathematics Nanjing University Nanjing China

Assessment of myocardial viability is essential in diagnosis and treatment management of patients suffering from myocardial infarction, and classification of pathology on myocardium is the key to this assessment. This work defines a new task of medical image analysis, i.e., to perform myocardial pathology segmentation (MyoPS) combining three-sequence cardiac magnetic resonance (CMR) images, which was first proposed in the MyoPS challenge, in conjunction with MICCAI 2020. The challenge provided 45 paired and pre-aligned CMR images, allowing algorithms to combine the complementary information from the three CMR sequences for pathology segmentation. In this article, we provide details of the challenge, survey the works from fifteen participants and interpret their methods according to five aspects, i.e., preprocessing, data augmentation, learning strategy, model architecture and post-processing. In addition, we analyze the results with respect to different factors, in order to examine the key obstacles and explore potential of solutions, as well as to provide a benchmark for future research. We conclude that while promising results have been reported, the research is still in the early stage, and more in-depth exploration is needed before a successful application to the clinics. Note that MyoPS data and evaluation tool continue to be publicly available upon registration via its homepage (***/zhuangxiahai/0/myops20/). © 2022, CC BY-NC-SA.

关键词： Magnetic resonance imaging

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AN OVERVIEW OF THE ROLE OF THE NAVSEA HUMAN-FACTORS engineering PROGRAM IN SHIP DESIGN

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NAVAL ENGINEERS JOURNAL 1983年第4期95卷 139-152页

作者： STEIN, NI BENEL, RA MALONE, TB Mr. Norman I. Stein:received his degree in mechanical engineering from the University of Iowa in 1943. MK Stein began his career with the Bureau of Ships Department of the Navy. After his military service with the Army of Occupation in Japan he has held positions with the Corps of Engineering Atomic Energy Commission Walter Reed Army General Hospital and the Protective Structures Development Center Department of the Army. He returned to the Naval Sea Systems Command in 1967 and is currently with the Manning and Controls Integration Branch SEA 55 W16. Mr. Stein is a registered professional engineer in New York state and also is a certified fallout shelter analyst with the Department of the Army. He has authored a comprehensive study on air distribution studies in multi-room shelters presentedpapers on human factors engineering to the Association of Scientists and Engineers and recently contributed a chapter on human factors engineering which will be incorporated in the proposed Naval Sea Systems Handbook on Surface Ship Design. Russell A. Benel:received his Ph. D. in engineering psychology from the University of Illinois at Urbana-Champaign. He is currently a Senior Research Scientist with Essex Corporation where he is the manager of the Man-Machine Systems Department. He has been responsible f o r scientific studies associated with the Human Factors Engineering f o r ships program under contract to the Naval Sea Systems Command specifically the development application and validation of human factors engineering technology f o r surface ship systems such as aircraft launch and recovery propulsion engineering combat direction weapons and total ship systems. He is currently providing Human Factors Engineering Support on the DDG-51. His other activities include a variety of research development test and evaluation activities for military systems. He had been with the Crew Performance Branch of the Crew Technology Division at the USAF School of Aerospace Medicine as a National Research Council Postd

This paper provides a context within which the role of human factors engineering (HFE) for Naval ship design may be understood. HFE is defined and its history as part of engineering design teams is traced. The role of HFE in ship systems design is defined, and the HFE technology for Ships Program, managed by SEA 061R, is described. The rationale for inclusion of HFE in the design process is presented, the methodology whereby it is incorporated into the design process is detailed, methodology to assess the application of HFE is outlined, and the benefits that will accrue as a result of inclusion of HFE considerations in the design process are documented. The counterpoint to inclusion is illustrated through instances of design-induced human errors. A specific application of HFE in the acquisition process is illustrated through use of the Landing Craft, Air Cushion HFE program plan. The difficulties which may be encountered as the size of the target system expands are described. Potential roadblocks to the required incorporation of HFE are examined for their source and possible ameliorative steps.

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