Bowel Obstruction Detection and Localization on Abdominal CT with Deep Learning
基于深度学习的腹部CT图像中肠梗阻的检测与定位
Moritz Vandenhirtz, Andrea Agostini, Dana Belde, Mélanie Roschewitz, Ismaiel Chikh Bakri, Tilo Niemann, André Euler, Julia E Vogt
机构
*
Department of Computer Science ETH Zurich(苏黎世联邦理工学院计算机科学系)
;
Department of Radiology Kantonsspital Baden affiliated Hospital for Research and Teaching of the Faculty of Medicine of the University of Zurich(苏黎世大学医学院附属巴登州立医院放射科(巴登大学苏黎世医学院研究与教学附属医院))
;
Department of Forensic Medicine Zurich University of Zurich(苏黎世大学法医学系)
Energy-based Tissue Manifolds for Longitudinal Multiparametric MRI Analysis
基于能量的组织流形用于纵向多参数MRI分析
Kartikay Tehlan, Lukas Förner, Sina Wendrich, Nico Schmutzenhofer, Michael Frühwald, Matthias Wagner, Nassir Navab, Thomas Wendler
机构
*
Dept. of diagnostic and interventional Radiology and Neuroradiology, University Hospital Augsburg, Germany(诊断与介入放射科和神经放射科,奥格斯堡大学医院,德国)
;
Digital Medicine, University Hospital Augsburg, Germany(数字医学,奥格斯堡大学医院,德国)
;
Chair for Computer Aided Medical Procedures and Augmented Reality, Technical University of Munich, Germany(计算机辅助医疗程序与增强现实 chair,慕尼黑技术大学,德国)
;
Bavarian Center for Cancer Research (BZKF) Augsburg, Germany(巴伐利亚癌症研究中心(BZKF)奥格斯堡,德国)
;
Dept. of Pediatrics and Adolescent Medicine, University Hospital Augsburg, Germany(儿科和青少年医学科,奥格斯堡大学医院,德国)
;
Center for Advanced Analytics and Predictive Sciences, University of Augsburg, Germany(高级分析与预测科学中心,奥格斯堡大学,德国)
A Dual Path Framework with Hotspot Guided Fusion for Three Dimensional CT to PET Synthesis in Head and Neck Cancer
一种用于头颈癌三维CT到PET合成的热点引导融合双路径框架
Mohd Maaz Khan, Oluwaseyi Oderinde
机构
*
Advanced Molecular Imaging in Radiotherapy (AdMIRe) Research Laboratory, School of Health Sciences, Purdue University, West Lafayette, IN, 47907, USA(高级分子影像在放射治疗(AdMIRe)研究实验室,健康科学学院,普渡大学,西拉法叶,IN,47907,美国)
;
Department of Radiation Oncology, Indiana University School of Medicine, Indianapolis, IN 46202, USA(放射肿瘤学部,印第安纳大学医学院,印第安纳波利斯,IN,46202,美国)
Journal refR. Tian and K. Scheffler, Group-Patch Joint Compression: Compressing Dynamic B0 and Static RF Spatial Modulations Across k-Space Subregion Groups for Highly Accelerated MRI, Magnetic Resonance in Medicine (2026): 1-21
Joint Lossless Compression and Steganography for Medical Images via Large Language Models
通过大语言模型实现医学图像的联合无损压缩与隐写术
Pengcheng Zheng, Xiaorong Pu, Kecheng Chen, Jiaxin Huang, Meng Yang, Bai Feng, Yazhou Ren, Jianan Jiang, Chaoning Zhang, Yang Yang, Heng Tao Shen
机构
*
Center for Future Media and School of Computer Science and Engineering, University of Electronic Science and Technology of China(未来媒体中心和电子科技大学计算机科学与工程学院)
;
Department of Computer Science and Engineering, University of Electronic Science and Technology of China(计算机科学与工程学院,电子科技大学)
;
Department of Electrical Engineering, and the Center for Intelligent Multidimensional Data Analysis, City University of Hong Kong(电子工程系和智能多维数据分析中心,城市大学)
;
Department of Machine Learning, Mohamed bin Zayed University of Artificial Intelligence(机器学习系,Mohamed bin Zayed人工智能大学)
Diffusion Models in Medical Image Inpainting: Challenges, Solution Taxonomy, and Future Directions
医学图像修复中的扩散模型:挑战、解决方案分类及未来方向
Arthur Dantas Mangussi, Joana Cristo Santos, Ricardo Cardoso Pereira, Ana Carolina Lorena, Mário A. T. Figueiredo, Pedro Henriques Abreu
机构
*
Aeronautics Institute of Technology(航空技术学院)
;
Science and Technology Institute, Federal University of São Paulo(圣保罗联邦大学科学与技术研究所)
;
LASIGE, Faculdade de Ciências, Universidade de Lisboa(里斯本大学理学院LASIGE实验室)
;
University of Coimbra, CISUC/LASI – Centre for Informatics and Systems of the University of Coimbra(科英布拉大学CISUC/LASI - 科英布拉大学信息与系统中心)
;
Instituto Superior Técnico, Universidade de Lisboa, Instituto de Telecomunicações(里斯本大学高等技术学院、电信研究所)
CommentsThis manuscript was posted before obtaining the necessary approval from all responsible parties. At the request of the supervising author, we are withdrawing the manuscript
Active few-shot segmentation by reinforcing data selection
通过强化数据选择实现主动少样本分割
Chenlan Zhao, Benny Wong, Timothy F. Lundberg, Ahmed M. Elsayed, Abdallah Aljarkas, Hamad A. Aljamaan, Lynn Karam, Qianye Yang, Yipeng Hu, Claire C. Villette, Shaheer U. Saeed
机构
*
Centre for Bioengineering, School of Engineering and Materials Science, Queen Mary University of London(伦敦玛丽女王大学工程与材料科学学院生物工程中心)
;
Digital Environment Research Institute, Queen Mary University of London(伦敦玛丽女王大学数字环境研究所)
;
UCL Hawkes Institute(伦敦大学学院UCL霍克斯研究所;医学物理与生物医学工程系)
;
Department of Medical Physics and Biomedical Engineering, University College London(耶鲁大学生物与生物医学科学系)
;
Department of Biological and Biomedical Sciences, Yale University(牛津大学工程科学系生物医学工程研究所)
;
Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford
CommentsThis version of the contribution has been accepted for publication at ICAI 2026, after peer review but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections
Atlas 2 -- Foundation models for clinical deployment
Atlas 2 -- 临床应用的基础模型
Maximilian Alber, Timo Milbich, Alexandra Carpen-Amarie, Stephan Tietz, Jonas Dippel, Lukas Muttenthaler, Beatriz Perez Cancer, Alessandro Benetti, Panos Korfiatis, Elias Eulig, Jérôme Lüscher, Jiasen Wu, Sayed Abid Hashimi, Gabriel Dernbach, Simon Schallenberg, Neelay Shah, Moritz Krügener, Aniruddh Jammoria, Jake Matras, Patrick Duffy, Matt Redlon, Philipp Jurmeister, David Horst, Lukas Ruff, Klaus-Robert Müller, Frederick Klauschen, Andrew Norgan
机构
*
Aignostics, Germany(德国Aignostics公司)
;
Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, US(美国梅奥诊所实验室医学与病理学部门)
;
Department of Radiology, Mayo Clinic, Rochester MN, US(美国梅奥诊所放射学部门)
;
Department of Information Technology, Mayo Clinic, Rochester MN, US(美国梅奥诊所信息技术部门)
;
Mayo Clinic, Rochester MN, US(美国梅奥诊所)
;
Digital Pathology, Mayo Clinic, Rochester MN, US(美国梅奥诊所数字病理学部门)
;
Machine Learning Group, Technische Universität Berlin, Germany(德国柏林技术大学机器学习小组)
;
BIFOLD – Berlin Institute for the Foundations of Learning and Data, Germany(德国柏林学习与数据基础研究所)
;
Department of Artificial Intelligence, Korea University, Republic of Korea(韩国韩国大学人工智能系)
;
Max-Planck Institute for Informatics, Germany(德国马克斯·普朗克信息研究所)
;
German Cancer Research Center (DKFZ) & German Cancer Consortium (DKTK), Berlin & Munich Partner Sites, Germany(德国癌症研究中心(DKFZ)及德国癌症联盟(DKTK)柏林与慕尼黑合作站点)
;
Institute of Pathology, Ludwig-Maximilians-Universität München, Germany(德国慕尼黑路德维希-马克西米利安大学病理学研究所)
;
Institute of Pathology, Charité – Universitätsmedizin Berlin, Germany(德国柏林夏里特大学医学中心病理学研究所)
;
Bavarian Cancer Research Center (BZKF), Germany(德国巴伐利亚癌症研究中心(BZKF))
;
Helmholtz Munich, Germany(德国海德堡-慕尼黑亥姆霍兹中心)
;
Technical University Munich, Germany(德国慕尼黑技术大学)
MedKGent: A Large Language Model Agent Framework for Constructing Temporally Evolving Medical Knowledge Graph
MedKGent:用于构建随时间演变的医学知识图谱的大语言模型智能体框架
Duzhen Zhang, Zixiao Wang, Zhong-Zhi Li, Yahan Yu, Shuncheng Jia, Jiahua Dong, Haotian Xu, Xing Wu, Yingying Zhang, Tielin Zhang, Jie Yang, Xiuying Chen, Le Song
机构
*
Mohamed bin Zayed University of Artificial Intelligence(莫扎德大学人工智能学院)
;
University of Chinese Academy of Sciences(中国科学院大学)
;
Kyoto University(京都大学)
;
Tsinghua University(清华大学)
;
East China Normal University(华东师范大学)
;
Center for Excellence in Brain Science and Intelligence Technology(脑科学与智能技术卓越中心)
;
Brigham and Women’s Hospital, Harvard Medical School(哈佛医学院布里特妇女医院)
;
GenBio AI