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Online 4D Ultrasound-Guided Robotic Tracking Enables 3D Ultrasound Localisation Microscopy with Large Tissue Displacements

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IEEE Transactions on Medical Imaging 2025年

作者： Yan, Jipeng Tan, Qingyuan Kawara, Shusei Zhu, Jingwen Wang, Bingxue Toulemonde, Matthieu Liu, Honghai Tan, Ying Tang, Meng-Xing Imperial College London Ultrasound Lab for Imaging and Sensing Department of Bioengineering LondonSW7 2AZ United Kingdom Harbin Institute of Technology State Key Laboratory of Robotics and Systems Harbin150001 China Imperial College London Department of Bioengineering LondonSW7 2AZ United Kingdom University of Portsmouth School of Computing PortsmouthPO1 2UP United Kingdom University of Melbourne Department of Mechanical Engineering ParkvilleVIC3010 Australia

Super-Resolution Ultrasound (SRUS) imaging through localising and tracking microbubbles, also known as Ultrasound Localisation Microscopy (ULM), has demonstrated significant potential for reconstructing microvasculature and flows with sub-diffraction resolution in clinical diagnostics. However, imaging organs with large tissue movements, such as those caused by respiration, presents substantial challenges. Existing methods often require breath holding to maintain accumulation accuracy, which limits data acquisition time and ULM image saturation. To improve image quality in the presence of large tissue movements, this study introduces an approach integrating high-frame-rate ultrasound with online precise robotic probe control. Tested on a microvasculature phantom with slow but large translation motions, up to 5 mm/s and 20 mm- twice the aperture size of the matrix array used, our method achieved real-time tracking of the moving phantom and imaging volume rate at 85 Hz, keeping majority of the target volume in the imaging field of view. ULM images of the moving cross channels in the phantom were successfully reconstructed in post-processing, demonstrating the feasibility of super-resolution imaging under large tissue motions. This represents a significant step towards ULM imaging of organs with large motion. © 1982-2012 IEEE.

关键词： Motion tracking

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Lightweight and conformal acousto-ultrasonic sensing network for multi-scale structural health monitoring: A review

FlexMat

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FlexMat 2024年

作者： Yehai Li Shifeng Guo Zhongqing Su Keqin Ding Xian Jun Loh Shenzhen Key Laboratory of Smart Sensing and Intelligent Systems Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China University of Chinese Academy of Sciences Beijing China The Key Laboratory of Biomedical Imaging Science and System Chinese Academy of Sciences Shenzhen China Department of Mechanical Engineering The Hong Kong Polytechnic University Kowloon Hong Kong Technology Innovation Center of Structural Health Monitoring of State Market Regulation China Special Equipment Inspection & Research Institute Beijing China Institute of Materials Research and Engineering (IMRE) Agency for Science Technology and Research (A*STAR) Singapore Singapore

Structural health monitoring (SHM) has been increasingly investigated for decades. Different physical principles have been developed for damage identification, such as electronics, mechanics, magnetics, etc., with different coverage (i.e., global, large-area, and local monitoring) and sensitivity. Mechanical acousto-ultrasonic-based methods have formed a big family in SHM technologies. Multiple wave/resonance modes have been utilized for versatile SHM tasks. The permanently integrated sensing networks play a significant role in achieving a cost-effective and reliable SHM system, with major concerns including weight increase for large-scale deployment and conformity for complex geometry structures. In this review, typical acousto-ultrasonic sensors made of different material systems are discussed, along with advantages and limitations. Moreover, advanced network installation methods have been introduced, including surface-mounting with pre-integrated networks on substrates and in situ printing, and embedding with composite layup and metal additive manufacturing. Sensor versatility and usage in multi-scale SHM techniques are then highlighted. Different wave/resonance modes are transmitted and received with corresponding elements and network designs. In conclusion, this systematic review mainly covers a collection of acousto-ultrasonic sensors, two modalities of network installation, and their employment with various SHM methods, hopefully providing a useful guide to building lightweight and conformal networks with passive or active-passive sensors, and developing complete and reliable SHM strategies by integrating different damage identification methods on multiple scales.

关键词： acousto-ultrasonic conformal installation lightweight sensing networks structural health monitoring

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Variable admittance control improving stability in physical human-robot interaction

Variable admittance control improving stability in physical ...

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2018 IEEE International Conference on Information and Automation, ICIA 2018

作者： Bian, Feifei Li, Ruifeng Ren, Danmei Liang, Peidong State Key Lab of Robotics and Systems Harbin Institute of Technology 2 Yikuangjie Nangang Harbin Heilongjiang China Quanzhou HIT Institute of Engineering and Technology Quanzhou Fujian China

ISBN: (纸本)9781538680698

This paper presents a variable admittance controller for eliminating instability in physical Human-Robot Interaction. In order to predict the instability, human hand stiffness is estimated in real time by modeling the level of muscle co-contraction of the human's arms. A modified time-domain vibration index is then proposed based on the forces applied by the operator on the robot. The virtual damping coefficient in admittance controller is adjusted according to the human hand stiffness and the vibration index to ensure both the performance and stability of the interaction system. The proposed system is evaluated on an experimental set-up using an UR10 robot and the results demonstrate significant improvement in stable and low-effort cooperation. © 2018 IEEE.

关键词： Stability

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Neuro-adaptive tracking control for uncertain Euler-Lagrange systems with time-varying output constraints and obstacle avoidance

Neuro-adaptive tracking control for uncertain Euler-Lagrange...

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Chinese Control Conference (CCC)

作者： Zhi-Gang Zhou Xinwei Chen Ruifeng Li Xiao-Ning Shi Kuanchang Wen School of Electronic Information Jiangsu University of Science and Technology Zhenjiang P. R. China Industrial Robot Application of Fujian University Engineering Research Center Minjiang University Fuzhou P. R. China The State Key Lab of Robotics and Systems Harbin Institute of Technology Harbin P. R. China Fujian(Quanzhou)-HIT Research Institute of Engineering and Technology Quanzhou P. R. China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

This paper addresses the tracking control problem for uncertain Euler-Lagrange system with time-varying output constraints in an environment containing obstacles. First, a novel log-type attractive potential field is utilized to describe the trajectory tracking task with time-varying constraints, and a bounded artificial potential field is established to describe the obstacle avoidance task. Then, by incorporating the two artificial potential fields (APFs) into the dynamic surface control, a neuro-adaptive tracking control is designed for the uncertain Euler-Lagrange system, which can ensure the system to fulfill the trajectory track task within time-varying limit range while avoiding obstacles. Because the obstacle avoidance task has a higher priority, the proposed control scheme can also guarantee the obstacle avoiding task can be fulfilled first when it is conflicted with the trajectory tracking task. Numerical simulations are provided to demonstrate the efficacy of the control strategy.

关键词： Collision avoidance Task analysis Artificial neural networks Time-varying systems Service robots Trajectory tracking

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RF chain reduction for MIMO systems: A hardware prototype

arXiv

引用

arXiv 2019年

作者： Gong, Tierui Shlezinger, Nir Ioushua, Shahar Stein Namer, Moshe Yang, Zhijia Eldar, Yonina C. State Key Lab of Robotics Key Lab of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel School of Electrical Engineering Tel Aviv University Tel Aviv Israel Faculty of Electrical Engineering Technion Haifa Israel

RF chain circuits play a major role in digital receiver architectures, allowing passband communication signals to be processed in baseband. When operating at high frequencies, these circuits tend to be costly. This increased cost imposes a major limitation on future multiple-input multiple-output (MIMO) communication technologies. A common approach to mitigate the increased cost is to utilize hybrid architectures, in which the received signal is combined in analog into a lower dimension, thus reducing the number of RF chains. In this work we present a hardware prototype implementing analog combining for RF chain reduction. The prototype consists of a specially designed configurable combining board as well as a dedicated experimental setup. Our hardware prototype allows to evaluate the effect of analog combining in MIMO systems using actual communication signals. The experimental study, which focuses on channel estimation accuracy in MIMO channels, demonstrates that using the proposed prototype, the achievable channel estimation performance is within a small gap in a statistical sense from that obtained using a costly receiver in which each antenna is connected to a dedicated RF chain. Furthermore, in the considered scenarios, this gap becomes negligible when the reduction rate, i.e., the ratio of the number of RF chains to the number of antennas, is above 62.5%. Copyright © 2019, The Authors. All rights reserved.

关键词： Channel estimation

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An Early Stage Researcher's Primer on systems Medicine Terminology

Network and Systems Medicine

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Network and systems Medicine 2021年第1期4卷 2-50页

作者： Zanin, Massimiliano Aitya, Nadim A.A. Basilio, José Baumbach, Jan Benis, Arriel Behera, Chandan K. Bucholc, Magda Castiglione, Filippo Chouvarda, Ioanna Comte, Blandine Dao, Tien-Tuan Ding, Xuemei Pujos-Guillot, Estelle Filipovic, Nenad Finn, David P. Glass, David H. Harel, Nissim Iesmantas, Tomas Ivanoska, Ilinka Joshi, Alok Boudjeltia, Karim Zouaoui Kaoui, Badr Kaur, Daman Maguire, Liam P. McClean, Paula L. McCombe, Niamh De Miranda, João Luís Moisescu, Mihnea Alexandru Pappalardo, Francesco Polster, Annikka Prasad, Girijesh Rozman, Damjana Sacala, Ioan Sanchez-Bornot, Jose M. Schmid, Johannes A. Sharp, Trevor Solé-Casals, Jordi Spiwok, Vojtěch Spyrou, George M. Stalidzans, Egils Stres, Blaa Sustersic, Tijana Symeonidis, Ioannis Tieri, Paolo Todd, Stephen Van Steen, Kristel Veneva, Milena Wang, Da-Hui Wang, Haiying Wang, Hui Watterson, Steven Wong-Lin, Kongfatt Yang, Su Zou, Xin Schmidt, Harald H.H.W. Centro de Tecnología Biomédica Universidad Politécnica de Madrid Madrid Spain Intelligent Systems Research Centre School of Computing Engineering and Intelligent Systems Ulster University Ulster United Kingdom Center for Physiology and Pharmacology Institute of Vascular Biology and Thrombosis Research Medical University of Vienna Vienna Austria TUM School of Life Sciences Weihenstephan Technical University of Munich Freising Germany Holon Israel CNR National Research Council IAC Institute for Applied Computing Rome Italy Lab of Computing Medical Informatics and Biomedical Imaging Technologies School of Medicine Aristotle University of Thessaloniki Thessaloniki Greece Université Clermont Auvergne INRAE UNH Plateforme d'Exploration du Métabolisme MetaboHUB Clermont Clermont-Ferrand France Université de Technologie de Compiègne Compiègne France Labex MS2T Control of Technological Systems-of-Systems CNRS and Université de Technologie de Compiègne Compiègne France Faculty of Engineering University of Kragujevac Kragujevac Serbia Kragujevac Serbia Steinbeis Advanced Risk Technologies Institute Doo Kragujevac Kragujevac Serbia Pharmacology and Therapeutics School of Medicine Galway Neuroscience Centre National University of Ireland Galway Ireland School of Computing Ulster University Ulster United Kingdom Holon Israel Department of Mathematics and Natural Sciences Kaunas University of Technology Kaunas Lithuania Faculty of Computer Science and Engineering Ss. Cyril and Methodius University Skopje Macedonia Medicine Faculty Université Libre de Bruxelles CHU de Charleroi Charleroi Belgium Northern Ireland Centre for Stratified Medicine Biomedical Sciences Research Institute Ulster University Ulster United Kingdom Escola Superior de Tecnologia e Gestão Instituto Politécnico de Portalegre Portalegre Portugal Instituto Superior Técnico Universidade de Lisboa Lisboa Portugal Faculty of Automatic Control and Computers University Politehnica of B

Background: systems Medicine is a novel approach to medicine, that is, an interdisciplinary field that considers the human body as a system, composed of multiple parts and of complex relationships at multiple levels, and further integrated into an environment. Exploring systems Medicine implies understanding and combining concepts coming from diametral different fields, including medicine, biology, statistics, modeling and simulation, and data science. Such heterogeneity leads to semantic issues, which may slow down implementation and fruitful interaction between these highly diverse fields. Methods: In this review, we collect and explain more than100 terms related to systems Medicine. These include both modeling and data science terms and basic systems medicine terms, along with some synthetic definitions, examples of applications, and lists of relevant references. Results: This glossary aims at being a first aid kit for the systems Medicine researcher facing an unfamiliar term, where he/she can get a first understanding of them, and, more importantly, examples and references for digging into the topic. © Massimiliano Zanin et al., 2021;Published by Mary Ann Liebert, Inc. 2021.

关键词： Semantics

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REFUGE2 CHALLENGE: A TREASURE TROVE FOR MULTI-DIMENSION ANALYSIS AND EVALUATION IN GLAUCOMA SCREENING

arXiv

引用

arXiv 2022年

作者： Fang, Huihui Li, Fei Wu, Junde Fu, Huazhu Sun, Xu Son, Jaemin Yu, Shuang Zhang, Menglu Yuan, Chenglang Bian, Cheng Lei, Baiying Zhao, Benjian Xu, Xinxing Li, Shaohua Fumero, Francisco Sigut, José Almubarak, Haidar Bazi, Yakoub Guo, Yuanhao Zhou, Yating Baid, Ujjwal Innani, Shubham Guo, Tianjiao Yang, Jie Orlando, José Ignacio Bogunović, Hrvoje Zhang, Xiulan Xu, Yanwu The REFUGE2 Challenge Australia State Key Laboratory of Ophthalmology Zhongshan Ophthalmic Center Sun Yat-Sen University Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science Guangzhou China Intelligent Healthcare Unit Baidu Inc. Beijing China The Institute of High Performance Computing Agency for Science Technology and Research Singapore Yatiris Group PLADEMA Institute CONICET UNICEN Tandil Argentina Christian Doppler Lab for Artificial Intelligence in Retina Department of Ophthalmology and Optometry Medical University of Vienna Vienna Austria VUNO Inc Seoul Korea Republic of Tencent HealthCare Tencent Shenzhen China Computer Vision Institute College of Computer Science and Software Engineering of Shenzhen University Shenzhen China School of Biomedical Engineering Health Science Center Shenzhen University China Xiaohe Healthcare ByteDance Guangdong Guangzhou510000 China School of Biomedical Engineering Shenzhen University China College of Computer Science & Software Engineering Shenzhen University China Department of Computer Science and Systems Engineering Universidad de La Laguna Spain Saudi Electronic University Saudi Arabia King Saud University Saudi Arabia Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China SGGS Institute of Engineering and Technology India Institute of Medical Robotics Shanghai Jiao Tong University China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

With the rapid development of artificial intelligence (AI) in medical image processing, deep learning in color fundus photography (CFP) analysis is also evolving. Although there are some open-source, labeled datasets of CFPs in the ophthalmology community, large-scale datasets for screening only have labels of disease categories, and datasets with annotations of fundus structures are usually small in size. In addition, labeling standards are not uniform across datasets, and there is no clear information on the acquisition device. Here we release a multi-annotation, multi-quality, and multi-device color fundus image dataset for glaucoma analysis on an original challenge-Retinal Fundus Glaucoma Challenge 2nd Edition (REFUGE2). The REFUGE2 dataset contains 2000 color fundus images with annotations of glaucoma classification, optic disc/cup segmentation, as well as fovea localization. Meanwhile, the REFUGE2 challenge sets three sub-tasks of automatic glaucoma diagnosis and fundus structure analysis and provides an online evaluation framework. Based on the characteristics of multi-device and multi-quality data, some methods with strong generalizations are provided in the challenge to make the predictions more robust. This shows that REFUGE2 brings attention to the characteristics of real-world multi-domain data, bridging the gap between scientific research and clinical application. © 2022, CC BY-NC-ND.

关键词： Color

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Mercapto-functionalized scaffold improves perovskite buried interfaces for tandem photovoltaics

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Nature communications 2025年第1期16卷 4917页

作者： Jianan Wang Shuaifeng Hu He Zhu Sanwan Liu Zhongyong Zhang Rui Chen Junke Wang Chenyang Shi Jiaqi Zhang Wentao Liu Xia Lei Bin Liu Yongyan Pan Fumeng Ren Hasan Raza Qisen Zhou Sibo Li Longbin Qiu Guanhaojie Zheng Xiaojun Qin Zhiguo Zhao Shuang Yang Neng Li Jingbai Li Atsushi Wakamiya Zonghao Liu Henry J Snaith Wei Chen Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan China. Optics Valley Laboratory Hubei China. Clarendon Laboratory Department of Physics University of Oxford Oxford UK. Institute for Chemical Research Kyoto University Kyoto Japan. State Key Laboratory of Silicate Materials for Architectures Wuhan University of Technology Wuhan China. Department of Materials Science and Engineering Southern University of Science and Technology Shenzhen China. Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems Department of Mechanical and Energy Engineering SUSTech Energy Institute for Carbon Neutrality Southern University of Science and Technology Shenzhen China. Shanghai Synchrotron Radiation Facility (SSRF) Zhangjiang Lab Shanghai Advanced Research Institute Chinese Academy of Sciences Shanghai China. Huaneng Clean Energy Research Institute Beijing China. School of Materials Science and Engineering East China University of Science and Technology Shanghai China. Hoffmann Institute of Advanced Materials Shenzhen Polytechnic University Shenzhen China. Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan China. liuzonghao@***. Optics Valley Laboratory Hubei China. liuzonghao@***. Clarendon Laboratory Department of Physics University of Oxford Oxford UK. henry.snaith@physics.ox.ac.uk. Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan China. wnlochenwei@***. Optics Valley Laboratory Hubei China. wnlochenwei@***.

Tandem photovoltaics hold great potential to surpass the efficiency limit of single-junction solar cells. Detrimental structural defects and chemical reactions at buried interfaces of subcells considerably impede the performance of integrated tandems. Here, we devise a mercapto-functionalized mesoporous silica layer as a superstructure at the buried interface to modulate the crystallisation, eliminate nanovoids, passivate defects, and suppress the oxidation of Sn(II) in the tin-lead perovskite films, contributing substantially to reduce charge carrier losses and improve stability in positive-intrinsic-negative structured devices. Consequently, the tin-lead perovskite single-junction cells show efficiency values of up to 23.7% with the best open-circuit voltage of 0.89 V. With the enhanced subcells, our double-junction tandems show efficiency values of 29.6% (certified 29.5% and steady-state 28.7%) and 24.7% on solar cells and 11.3 cm mini-modules, respectively. Encapsulated tandems maintain 90% of initial efficiency after 445 h of maximum power point tracking under simulated 1-sun illumination.

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Corrections to “Iris Center Localization Using Energy Map With Image Inpaint Technology and Post-Processing Correction”

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IEEE Access 2020年 8卷 76595-76595页

作者： Lihong Dai Jinguo Liu Zhaojie Ju Yang Gao State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China School of Electronic and Information Engineering University of Science and Technology Liaoning Anshan China School of Computing University of Portsmouth Portsmouth U.K. Space Technology for Autonomous and Robotic Systems Laboratory (STAR LAB) Surrey Space Centre University of Surrey Guildford U.K.

In the above article [1] , the affiliations of authors Lihong Dai and Yang Gao need to be corrected. Moreover, the biography of Yang Gao needs to be corrected. The specific corrections are as follows.

关键词： Robots Biographies Aerospace electronics Automation Manufacturing Research and development Object recognition

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Data-driven Discovery of Cyber-Physical systems

arXiv

引用

arXiv 2018年

作者： Yuan, Ye Tang, Xiuchuan Pan, Wei Li, Xiuting Zhou, Wei Zhang, Hai-Tao Ding, Han Goncalves, Jorge School of Automation Huazhong University of Science and Technology State Key Lab of Digital Manufacturing Equipment and Technology School of Mechanical Science and Engineering Huazhong University of Science and Technology Department of Cognitive Robotics Delft University of Technology Department of Engineering University of Cambridge Luxembourg Centre for Systems Biomedicine University of Luxembourg

Cyber-physical systems (CPSs) embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, intelligent manufacture and medical monitoring. CPSs have proved resistant to modeling due to their intrinsic complexity arising from the combination of physical components and cyber components and the interaction between them. This study proposes a general framework for reverse engineering CPSs directly from data. The method involves the identification of physical systems as well as the inference of transition logic. It has been applied successfully to a number of real-world examples ranging from mechanical and electrical systems to medical applications. The novel framework seeks to enable researchers to make predictions concerning the trajectory of CPSs based on the discovered model. Such information has been proven essential for the assessment of the performance of CPS, the design of failure-proof CPS and the creation of design guidelines for new CPSs. Copyright © 2018, The Authors. All rights reserved.

关键词： Embedded systems

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