检索结果-内蒙古大学图书馆

arXiv 2023年

作者： Huang, Zhefeng Gunderman, Anthony L. Wilcox, Samuel E. Sengupta, Saikat Shah, Jay Lu, Aiming Woodrum, David Chen, Yue Institute of Robotics and Intelligent Machines Georgia Institute of Technology 801 Atlantic Dr NW AtlantaGA30332 United States Vanderbilt University Institute of Imaging Science Vanderbilt University Medical Center 1161 21st Ave South Medical Center North NashvilleTN37232 United States Department of Radiology Emory University 1364 Clifton Rd AtlantaGA30329 United States Department of Radiology Mayo Clinic 200 1st St SW RochesterMN55905 United States Department of Biomedical Engineering Georgia Institute of Technology Emory University 313 Ferst Dr 2127 AtlantaGA30332 United States

MR-guided microwave ablation (MWA) has proven effective in treating hepatocellular carcinoma (HCC) with small-sized tumors, but the state-of-the-art technique suffers from sub-optimal workflow due to speed and accuracy of needle placement. This paper presents a compact body-mounted MR-conditional robot that can operate in closed-bore MR scanners for accurate needle guidance. The robotic platform consists of two stacked Cartesian XY stages, each with two degrees of freedom, that facilitate needle guidance. The robot is actuated using 3D-printed pneumatic turbines with MR-conditional bevel gear transmission systems. Pneumatic valves and control mechatronics are located inside the MRI control room and are connected to the robot with pneumatic transmission lines and optical fibers. Free space experiments indicated robot-assisted needle insertion error of 2.6±1.3 mm at an insertion depth of 80 mm. The MR-guided phantom studies were conducted to verify the MR-conditionality and targeting performance of the robot. Future work will focus on the system optimization and validations in animal trials. Copyright © 2023, The Authors. All rights reserved.

关键词： Degrees of freedom (mechanics)

来源：评论

学校读者我要写书评

暂无评论

Safer Motion Planning of Steerable Needles via a Shaft-to-Tissue Force Model

引用

Journal of Medical robotics Research 2023年第1-2期8卷

作者： Bentley, Michael Rucker, Caleb Reddy, Chakravarthy Salzman, Oren Kuntz, Alan Robotics Center and Kahlert School of Computing University of Utah Salt Lake City 84112 UT United States The Department of Mechanical Aerospace and Biomedical Engineering University of Tennessee Knoxville 37996 TN United States Huntsman Cancer Institute and School of Medicine University of Utah Salt Lake City 84112 UT United States Department of Computer Science Technion-Israel Institute of Technology Technion City Haifa 3200003 Israel

Steerable needles are capable of accurately targeting difficult-to-reach clinical sites in the body. By bending around sensitive anatomical structures, steerable needles have the potential to reduce the invasiveness of many medical procedures. However, inserting these needles with curved trajectories increases the risk of tissue damage due to perpendicular forces exerted on the surrounding tissue by the needle's shaft, potentially resulting in lateral shearing through tissue. Such forces can cause significant tissue damage, negatively affecting patient outcomes. In this work, we derive a tissue and needle force model based on a Cosserat string formulation, which describes the normal forces and frictional forces along the shaft as a function of the planned needle path, friction model and parameters, and tip piercing force. We propose this new force model and associated cost function as a safer and more clinically relevant metric than those currently used in motion planning for steerable needles. We fit and validate our model through physical needle robot experiments in a gel phantom. We use this force model to define a bottleneck cost function for motion planning and evaluate it against the commonly used path-length cost function in hundreds of randomly generated three-dimensional (3D) environments. Plans generated with our force-based cost show a 62% reduction in the peak modeled tissue force with only a 0.07% increase in length on average compared to using the path-length cost in planning. Additionally, we demonstrate planning with our force-based cost function in a lung tumor biopsy scenario from a segmented computed tomography (CT) scan. By directly minimizing the modeled needle-to-tissue force, our method may reduce patient risk and improve medical outcomes from steerable needle interventions. © 2023 World Scientific Publishing Company.

关键词： bottleneck cost function continuum robots Force modeling motion planning robotic needle steering

来源：评论

学校读者我要写书评

暂无评论

Localizing oscillatory sources in a brain by MEG data during cognitive activity

Localizing oscillatory sources in a brain by MEG data during...

引用

International Conference on Computational Intelligence and Networks (CINE)

作者： Semen Kurkin Alexander Hramov Parth Chholak Alexander Pisarchik Neuroscience and Cognitive Techology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Center for Biomedical Technology Technical University of Madrid Madrid Spain

ISBN: (数字)9781728156880

ISBN: (纸本)9781728156897

The present work demonstrates the features and basic steps of applying the Dynamic Imaging of Coherent Sources (DICS) technique for Localizing oscillatory sources in a brain by MEG data during cognitive activity. As the example, we consider the problem of identification of the sources responsible for producing this oscillatory activity registering in the MEG experiment during the visual processing in a brain. The DICS technique has been shown to be effective in terms of localizing a region of activity in a brain related to cognitive processes. It revealed the areas in the occipital part of the brain that are responsible for processing visual stimuli. This approach allows one to obtain additional important information in the analysis of MEG data.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Low-Friction Soft Robots for Targeted Bacterial Infection Treatment in Gastrointestinal Tract

引用

类生命系统（英文） 2024年第5期2024卷 299-313页

作者： Ben Wang Yunrui Chen Zhicheng Ye Haidong Yu Kai Fung Chan Tiantian Xu Zhiguang Guo Weimin Liu Li Zhang College of Chemistry and Environmental Engineering Shenzhen UniversityShenzhen 518060China Guangxi Key Laboratory of Processing for Non-Ferrous Metals and Featured Materials School of ResourceEnvironments and MaterialsGuangxi UniversityNanning 530004China Chow Yuk Ho Technology Centre for Innovative Medicine The Chinese University of Hong KongShatinNew TerritoriesHong Kong SARChina Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Key Laboratory of Biomedical Imaging Science and System Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Hubei Collaborative Innovation Centre for Advanced Organic Chemical Materials and Ministry of Education Key Laboratory for the Green Preparation and Application of Functional Materials Hubei UniversityWuhan 430062China State Key Laboratory of Solid Lubrication Lanzhou Institute of Chemical PhysicsChinese Academy of ScienceLanzhou 730000China State Key Laboratory of Solid Lubrication Lanzhou Institute of Chemical PhysicsChinese Academy of ScienceLanzhou 730000China Department of Mechanical and Automation Engineering The Chinese University of Hong KongShatinNew TerritoriesHong Kong SARChina Multi-Scale Medical Robotics Center Hong Kong Science ParkShatinNew TerritoriesHong Kong SARChina

Untethered and self-transformable miniature robots are capable of performing reconfigurable deformation and on-demand locomotion,which aid the traversal toward various lumens,and bring revolutionary changes for targeted delivery in gastrointestinal(GI)***,the viscous non-Newtonian liquid environment and plicae gastricae obstacles severely hamper high-precision actuation and payload ***,we developed a low-friction soft robot by assembly of densely arranged cone structures and grafting of hydrophobic *** magnetic orientation encoded robot can move in multiple modes,with a substantially reduced drag,terrain adaptability,and improved motion velocity across the non-Newtonian ***,the robot stiffness can be reversibly controlled with magnetically induced hardening,enabling on-site scratching and destruction of antibiotic-ineradicable polymeric matrix in biofilms with a low-frequency magnetic ***,the magnetocaloric effect can be utilized to eradicate the bacteria by magnetocaloric effect under high-frequency alternating *** verify the potential applications inside the body,the clinical imaging-guided actuation platforms were developed for vision-based control and delivery of the *** developed low-friction robots and clinical imaging-guided actuation platforms show their high potential to perform bacterial infection therapy in various lumens inside the body.

关键词： astro gast bacterial infection intestinal low-friction robots soft targeted tract

来源：评论

学校读者我要写书评

暂无评论

Machine learning approaches for classification of imaginary movement type by MEG data for neurorehabilitation 3

Machine learning approaches for classification of imaginary ...

引用

3rd School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2019

作者： Kurkin, Semen Chholak, Parth Maksimenko, Vladimir Pisarchik, Alexander Neuroscience and Cognitive Techology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Center for Biomedical Technology Technical University of Madrid Madrid Spain

ISBN: (纸本)9781728124704

The conducted magnetoencephalographic (MEG) experiments with voluntary participants confirm the existence of two types of motor imagery, kinesthetic imagery (KI) and visual imagery (VI), distinguished by activation and inhibition of different brain areas. Similar to real movement, KI implies muscular sensation when performing an imaginary moving action that leads to event-related desynchronization (ERD) of motor-associated brain rhythms. By contrast, VI refers to visualization of the corresponding action that results in event-related synchronization (ERS) of α- and β-wave activity. A notable difference between KI and VI groups occurs in the frontal brain area. The application of artificial neural networks allows us to classify MI in raising right and left arms with average accuracy of 70% for both KI and VI using appropriate filtration of input signals. © 2019 IEEE.

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Surgical robotic technology for developing an Endonasal Endoscopic Transsphenoidal Surgery (EETS) robotic system

引用

Open Neurology Journal 2019年第1期13卷 96-106页

作者： Chumnanvej, Sorayouth Pillai, Branesh M. Suthakorn, Jackrit Neurosurgery Division Department of Surgery Faculty of Medicine Ramathibodi Hospital Mahidol University Bangkok Thailand Center for Biomedical and Robotics Technology (BART LAB) Department of Biomedical Engineering Faculty of Engineering Mahidol University Salaya Thailand

Purpose: Neurosurgical robots are acknowledged for their advantages in assisting neurosurgeons in enhancing their precision and accuracy. Here, the aim of this study is to report the first use as a robot-assisted Endonasal Endoscopic Transsphenoidal (EET) approach, applied to reach sphenoid sinus in a cadaver. The introduction of the seven tenets for the Endonasal Endoscopic Transsphenoidal approach will propel the feasibility of neurosurgical techniques and instruments for intrasellar lesions. Methods: Endonasal endoscopic transsphenoidal approach in a cadaver was performed under robot assistance with simple navigation system. This preliminary study reveals the accuracy and precision of the robot to reach a target at sphenoid sinus safely and within the shortest duration . Results: This robotic technology provided the foundation to support neurosurgeons when they are working in narrow and complicated surgical corridors with accuracy and precision. Conclusion: This article reveals the first robot-assisted Endonasal Endoscopic Transsphenoidal approach. This demonstrates the feasibility of the evolution and will augment neurosurgeons toward their limits of minimally invasive surgical techniques, manual dexterity, and spatial orientation. These tenets will be as state of the art and overcome the future challenges of Endonasal Endoscopic Transsphenoidal approach shortly. © 2019 Chumnanvej et al.

关键词： Endoscopic Endonasal Transphenoid (EET) Medical robotics Minimally invasive surgery Neurosurgical robots Pituitary adenoma Robotic surgery

来源：评论

学校读者我要写书评

暂无评论

CholecTriplet2022: Show me a tool and tell me the triplet - an endoscopic vision challenge for surgical action triplet detection

arXiv

引用

arXiv 2023年

作者： Nwoye, Chinedu Innocent Yu, Tong Sharma, Saurav Murali, Aditya Alapatt, Deepak Vardazaryan, Armine Yuan, Kun Hajek, Jonas Reiter, Wolfgang Yamlahi, Amine Smidt, Finn-Henri Zou, Xiaoyang Zheng, Guoyan Oliveira, Bruno Torres, Helena R. Kondo, Satoshi Kasai, Satoshi Holm, Felix Özsoy, Ege Gui, Shuangchun Li, Han Raviteja, Sista Sathish, Rachana Poudel, Pranav Bhattarai, Binod Wang, Ziheng Rui, Guo Schellenberg, Melanie Vilaça, João L. Czempiel, Tobias Wang, Zhenkun Sheet, Debdoot Thapa, Shrawan Kumar Berniker, Max Godau, Patrick Morais, Pedro Regmi, Sudarshan Tran, Thuy Nuong Fonseca, Jaime Nölke, Jan-Hinrich Lima, Estevão Vazquez, Eduard Maier-Hein, Lena Navab, Nassir Mascagni, Pietro Seeliger, Barbara Gonzalez, Cristians Mutter, Didier Padoy, Nicolas ICube University of Strasbourg CNRS France Riwolink GmbH Germany Heidelberg Germany Heidelberg Germany Institute of Medical Robotics School of Biomedical Engineering Shanghai Jiao Tong University China 2Ai School of Technology IPCA Barcelos Portugal School of Medicine University of Minho Braga Portugal Algoritimi Center School of Engineering University of Minho Guimeraes Portugal Muroran Institute of Technology Japan Niigata University of Health and Welfare Japan Technical University Munich Germany Southern University of Science and Technology China Indian Institute of Technology Kharagpur India University College London United Kingdom University of Aberdeen United Kingdom Redev Technology Ltd United Kingdom Nepal Intuitive Surgical United States Fondazione Policlinico Universitario Agostino Gemelli IRCCS Rome Italy University Hospital of Strasbourg France IHU Strasbourg France

Formalizing surgical activities as triplets of the used instruments, actions performed, and target anatomies is becoming a gold standard approach for surgical activity modeling. The benefit is that this formalization helps to obtain a more detailed understanding of tool-tissue interaction which can be used to develop better Artificial Intelligence assistance for image-guided surgery. Earlier efforts and the CholecTriplet challenge introduced in 2021 have put together techniques aimed at recognizing these triplets from surgical footage. Estimating also the spatial locations of the triplets would offer a more precise intraoperative context-aware decision support for computer-assisted intervention. This paper presents the CholecTriplet2022 challenge, which extends surgical action triplet modeling from recognition to detection. It includes weakly-supervised bounding box localization of every visible surgical instrument (or tool), as the key actors, and the modeling of each tool-activity in the form of triplet. The paper describes a baseline method and 10 new deep learning algorithms presented at the challenge to solve the task. It also provides thorough methodological comparisons of the methods, an in-depth analysis of the obtained results across multiple metrics, visual and procedural challenges;their significance, and useful insights for future research directions and applications in surgery. © 2023, CC BY-NC-SA.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

A Long Short-term Memory Based Recurrent Neural Network for Interventional MRI Reconstruction

arXiv

引用

arXiv 2022年

作者： Zhao, Ruiyang He, Zhao Wang, Tao Qiu, Suhao Herman, Pawel Hu, Yanle Zhang, Chencheng Shen, Dinggang Sun, Bomin Yang, Guang-Zhong Feng, Yuan School of Biomedical Engineering Shanghai Jiao Tong University Shanghai200240 China Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign UrbanaIL United States Department of Neurosurgery Center for Functional Neurosurgery Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China Division of computational science and technology KTH Royal Institute of Technology Stockholm Sweden Department of Radiation Oncology Mayo Clinic in Arizona PhoenixAZ United States School of Biomedical Engineering ShanghaiTech University Shanghai201210 China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China

Interventional magnetic resonance imaging (i-MRI) for surgical guidance could help visualize the interventional process such as deep brain stimulation (DBS), improving the surgery performance and patient outcome. Different from retrospective reconstruction in conventional dynamic imaging, i-MRI for DBS has to acquire and reconstruct the interventional images sequentially online. Here we proposed a convolutional long short-term memory (Conv-LSTM) based recurrent neural network (RNN), or ConvLR, to reconstruct interventional images with golden-angle radial sampling. By using an initializer and Conv-LSTM blocks, the priors from the preoperative reference image and intra-operative frames were exploited for reconstructing the current frame. Data consistency for radial sampling was implemented by a soft-projection method. To improve the reconstruction accuracy, an adversarial learning strategy was adopted. A set of interventional images based on the pre-operative and postoperative MR images were simulated for algorithm validation. Results showed with only 10 radial spokes, ConvLR provided the best performance compared with state-of-the-art methods, giving an acceleration up to 40 folds. The proposed algorithm has the potential to achieve real-time i-MRI for DBS and can be used for general purpose MR-guided intervention. Copyright © 2022, The Authors. All rights reserved.

关键词： Image reconstruction

来源：评论

学校读者我要写书评

暂无评论

Balance Assessment for Double and Single Leg Stance Using FIBOD Balance System 3rd

Balance Assessment for Double and Single Leg Stance Using FI...

引用

3rd International Conference for Innovation in biomedical Engineering and Life Sciences, ICIBEL 2020

作者： Khor, Kang Xiang Yeong, Che Fai Su, Eileen Lee Ming Latip, Hadafi Fitri Mohd Khor, Yvonne Yee Woon Chan, Sook Chin Chern, Phei Ming Leow, Mei Lian Abdullah, Najib bin Mustar, Muhammad Farhan bin Halim, Muhammad Nurhakim bin Abdul Skudai Johor81300 Malaysia Center of Artificial Intelligence and Robotics UTM Kuala Lumpur54100 Malaysia School of Biomedical Engineering and Health Science Faculty of Engineering UTM Skudai Johor81310 Malaysia Sports Innovation and Technology Centre UTM Skudai Johor81300 Malaysia UTM Skudai Johor81310 Malaysia MAHSA University Jenjarom Selangor42610 Malaysia Clinical Research Centre Cheras Rehabilitation Hospital Kuala Lumpur56000 Malaysia Faculty of Computer and Mathematical Sciences UiTM Segamat85000 Malaysia

ISBN: (纸本)9783030650919

Physical balance is important to support human motion for almost all activities of daily living such as standing, sitting, cooking, housework or shopping. However, balance tends to drop as human grow older due to the loss of muscle. FIBOD balance system (FBS) is a balance system designed to be portable and easy to use. This study investigates the FBS balance measures with 17 healthy subjects. Results show significant differences in double-leg overall stability index (OSI) and medial-lateral stability index (MLSI) (p = 0.01);double-leg and dominant leg MLSI (p © 2021, Springer Nature Switzerland AG.

关键词： Balance assessment Balance board Instrumented wobble board

来源：评论

学校读者我要写书评

暂无评论

Hair Direction Detection*

Hair Direction Detection*

引用

WRC Symposium on Advanced robotics and Automation (WRC SARA)

作者： Peng Ba Pengyi Wang Hongde Wu Qian Yang Yongqiang Feng Junchen Wang Yida David Hu Changsheng Li Wenyong Liu Shaolong Kuang Bai-Quan Su Medical Robotics Laboratory School of Intelligent Engineering and Automation Beijing University of Posts and Telecommunications Beijing China Plastic Surgery Hospital Chinese Academy of Medical Sciences and Peking Union Medical College Beijing China School of Mechanical Engineering and Automation Beihang University Beijing China Brigham and Women’s Hospital Harvard Medical School Boston MA USA School of Mechatronical Engineering Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Key Laboratory for Biomechanics and Mechanobiology of Chinese Education Ministry Beijing Advanced Innovation Centre for Biomedical Engineering School of Biological Science and Medical Engineering Beihang University Beijing China School of Health Science and Environmental Engineering Shenzhen University of Technology Shenzhen China

ISBN: (数字)9798331506100

ISBN: (纸本)9798331506117

Hair direction is an important external feature of hair, and recognising hair direction is a prerequisite for processing hair. In this paper, a new algorithm is proposed and systematically verified experimentally for the problem of recognising hair direction. The main goal of this paper is to develop an algorithm that can identify hair direction in a complex image environment. A curve segment analysis method based on image skeletonisation is adopted, which is based on skeleton extraction, intersection identification, curve segmentation and direction prediction. In addition, this paper combines the technique of non-maximal value suppression and PCA analysis to improve the accuracy and stability of the estimation. In the experimental design, this paper chooses a representative image dataset to verify the effectiveness of this paper's algorithm. The experimental process includes the steps of image preprocessing, skeletonisation processing, intersection detection and merging, and direction prediction. The experimental results show that the method in this paper can accurately and effectively identify the hair direction. The main contribution of this paper is to propose a new hair direction recognition method and experimentally verify its effectiveness and accuracy in complex backgrounds.

关键词： Hair Image segmentation Accuracy Three-dimensional displays Merging Prediction algorithms Stability analysis

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：