Goal-conditioned reinforcement learning for ultrasound navigation guidance
King’s College London（伦敦国王学院）；Siemens Healthcare Limited（西门子医疗有限公司）；Siemens Healthineers（西门子医疗）；Siemens Healthineers AG（西门子医疗股份公司）；Carol Davila University of Medicine and Pharmacy Bucharest（布加勒斯特卡罗尔·达维拉医药大学）；Fortis Institute of Medical Sciences（富蒂斯医学院）；Guy’s and St Thomas’ NHS Foundation Trust（盖伊和圣托马斯国民保健信托基金）
Abdoul Aziz Amadou, Vivek Singh, Florin C. Ghesu, Young-Ho Kim, Laura Stanciulescu, Harshitha P. Sai, Puneet Sharma, Alistair Young, Ronak Rajani, Kawal Rhode
Transesophageal echocardiography (TEE) plays a pivotal role in cardiology for diagnostic and interventional procedures. However, using it effectively requires extensive training due to the intricate nature of image acquisition and interpretation. To enhance the efficiency of novice sonographers and reduce variability in scan acquisitions, we propose a novel ultrasound (US) navigation assistance method based on contrastive learning as goal-conditioned reinforcement learning (GCRL). We augment the previous framework using a novel contrastive patient batching method (CPB) and a data-augmented contrastive loss, both of which we demonstrate are essential to ensure generalization to anatomical variations across patients. The proposed framework enables navigation to both standard diagnostic as well as intricate interventional views with a single model. Our method was developed with a large dataset of 789 patients and obtained an average error of 6.56 mm in position and 9.36 degrees in angle on a testing dataset of 140 patients, which is competitive or superior to models trained on individual views. Furthermore, we quantitatively validate our method's ability to navigate to interventional views such as the Left Atrial Appendage (LAA) view used in LAA closure. Our approach holds promise in providing valuable guidance during transesophageal ultrasound examinations, contributing to the advancement of skill acquisition for cardiac ultrasound practitioners.
Autonomous Navigation of an Ultrasound Probe Towards Standard Scan Planes with Deep Reinforcement Learning
The Chinese University of Hong Kong（香港中文大学）；Shenzhen University（深圳大学）；Sonoscape Medical Corp.（开立医疗）；Peking University Shenzhen Hospital（北京大学深圳医院）；Southern University of Science and Technology（南方科技大学）；Shenzhen Research Institute of the Chinese University of Hong Kong（香港中文大学深圳研究院）
Image-Guided Navigation of a Robotic Ultrasound Probe for Autonomous Spinal Sonography Using a Shadow-aware Dual-Agent Framework
The Chinese University of Hong Kong（香港中文大学）；Shenzhen University（深圳大学）；Southern University of Science and Technology（南方科技大学）；Shenzhen Research Institute of the Chinese University of Hong Kong（香港中文大学深圳研究院）
DINO-CVA: A Multimodal Goal-Conditioned Vision-to-Action Model for Autonomous Catheter Navigation
Gina Cody School of Engineering and Computer Science, Concordia University（甘娜·柯迪工程与计算机科学学院，康科迪亚大学）；The Wilfred and Joyce Posluns Centre for Image Guided Innovation & Therapeutic Intervention (PCIGITI) at the Hospital for Sick Children (SickKids)（威廉与乔伊斯·波斯卢斯影像引导创新与治疗干预中心（PCIGITI）（SickKids医院））；Electrical and Computer Engineering Department, Kettering University（电气与计算机工程系，凯特林大学）
Language-Conditioned World Modeling for Visual Navigation
University of Washington（华盛顿大学）；National University of Singapore（新加坡国立大学）；Clemson University（克莱姆森大学）；Drexel University（德雷塞尔大学）；Microsoft Research（微软研究院）
PathPilot: An Adaptive Question-Conditioned Multi-Magnification Navigation Agent for Whole-Slide Image Analysis
Technical University of Munich（慕尼黑工业大学）；Munich Center for Machine Learning（慕尼黑机器学习中心）；Chair of Computer Aided Medical Procedures, Technical University of Munich（慕尼黑工业大学计算机辅助医疗程序讲席）；Juntendo University Graduate School of Medicine（顺天堂大学医学院）；Dalian University of Technology（大连理工大学）；University of Science and Technology of China（中国科学技术大学）；Munich Data Science Institute, Technical University of Munich（慕尼黑工业大学慕尼黑数据科学研究所）
Instruction-as-State: Environment-Guided and State-Conditioned Semantic Understanding for Embodied Navigation
National Key Laboratory of Human-Machine Hybrid Augmented Intelligence（人机混合增强智能国家重点实验室）；The Institute of Artificial Intelligence and Robotics（人工智能与机器人研究所）；School of Information Science and Technology（信息科学与技术学院）；Zhongguancun Academy（中关村学院）
Chair for Computer-Aided Medical Procedures and Augmented Reality, Technical University of Munich（计算机辅助医学程序与增强现实 chair，慕尼黑技术大学）；Munich Center for Machine Learning（慕尼黑机器学习中心）；The University of Hong Kong（香港大学）
Shape Completion and Real-Time Visualization in Robotic Ultrasound Spine Acquisitions
Computer Aided Medical Procedures, Technical University of Munich（技术大学慕尼黑计算机辅助医疗程序）；Konrad Zuse School of Excellence in Reliable AI (relAI)（Konrad Zuse卓越人工智能学校）；Munich Center for Machine Learning (MCML)（慕尼黑机器学习中心）
Map the Possibilities: Spatial Belief Fields for Language-Goal Aerial Navigation
National University of Defense Technology（国防科技大学）；State Key Laboratory of Digital Intelligent Modeling and Simulation（数字智能建模与仿真国家重点实验室）；Zhejiang University（浙江大学）
NavMapFusion: Diffusion-based Fusion of Navigation Maps for Online Vectorized HD Map Construction
Mercedes-Benz Research & Development North America, USA（梅赛德斯-奔驰北美研究与开发）；University of Stuttgart, Germany（斯图加特大学）；University of California, San Diego, USA（加州大学圣地亚哥分校）；University of Southampton, United Kingdom（南安普顿大学）
PreAct-Nav: Agentic Reasoning Before Action for Urban Navigation
Shanghai Jiao Tong University（上海交通大学）；Beihang University（北京航空航天大学）；The Hong Kong University of Science and Technology（香港科技大学）；Tsinghua University（清华大学）；University of Cambridge（剑桥大学）；Intelligent Game and Decision Lab (IGDL)（智能博弈与决策实验室）
Freehand Ultrasound Image Simulation with Spatially-Conditioned Generative Adversarial Networks
Centre for Medical Image Computing, University College London（伦敦大学学院医学图像计算中心）；Institute of Biomedical Engineering, University of Oxford（牛津大学生物医学工程研究所）；Department of Diagnostic Imaging, Royal Free London NHS Foundation Trust（伦敦皇家自由NHS基金会信托诊断影像科）
Action-Conditioned Risk Gating for Safety-Critical Control under Partial Observability
University of Virginia（弗吉尼亚大学）；Google（谷歌）；University of Maryland, College Park（马里兰大学 College Park 分校）；Stanford University（斯坦福大学）；Louisiana State University（路易斯安那州立大学）；College of William and Mary（威廉与玛丽学院）
Dual Conditioned Diffusion Models for Out-Of-Distribution Detection: Application to Fetal Ultrasound Videos
Institute of Biomedical Engineering, University of Oxford（牛津大学生物医学工程研究所）；Nuffield Department of Women’s and Reproductive Health, University of Oxford（牛津大学纳菲尔德妇女与生殖健康系）
Diffusion as Reasoning: Enhancing Object Navigation via Diffusion Model Conditioned on LLM-based Object-Room Knowledge
State Key Laboratory of Robotics and Systems, Harbin Institute of Technology, Harbin 150001, China（机器人系统国家重点实验室，哈尔滨工业大学，哈尔滨）；School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore 639798, Singapore（机械与航空航天工程学院，南洋理工大学，新加坡）
VA-Adapter: Adapting Ultrasound Foundation Model to Echocardiography Probe Guidance
Department of Automation, BNRist, Tsinghua University, Beijing, China（自动化系、BNRist、清华大学、北京、中国）；School of Computer Science and Technology, Xidian University（计算机科学与技术学院、西安电子科技大学）；Beijing Academy of Artificial Intelligence（北京人工智能研究院）；Chinese PLA General Hospital（中国人民解放军总医院）
Multivariate Gaussian NeRF for Wide Field-of-View Ultrasound Reconstruction
Chair for Computer Aided Medical Procedures (CAMP), Technical University of Munich, Germany（计算机辅助医学程序系（CAMP），慕尼黑技术大学，德国）；Munich Center for Machine Learning (MCML), Munich, Germany（慕尼黑机器学习中心，慕尼黑，德国）；LUMA Vision, Beech Hill Road, Dublin, Ireland（LUMA视觉，Beech Hill Road，都柏林，爱尔兰）
