검색어 : 통합검색[Markl Jun]
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- An Homogenitat und Farbe gewonnen: Jun Markl und das MDR Sinfonieorchester uberzeugen nicht nur durch eine interessante Vernetzung der Programme
- Bohme-Mehner, T.; ; (Das Orchester, v.57, 2009, pp.45)
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- Aortic Viscous Energy Loss for Assessment of Valve-related Hemodynamics in Asymptomatic Severe Aortic Stenosis
- Shan, Yan; Li, Jun; Wu, Boting; Barker, Alex J.; Markl, Michael; Lin, Jiang; Shu, Xianhong; Wang, Yongshi; ; (Radiology. Cardiothoracic imaging, v.4, 2022, pp.e220010)
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- MRI-MECH: mechanics-informed MRI to estimate esophageal health
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Halder, Sourav;
Johnson, Ethan M.;
Yamasaki, Jun;
Kahrilas, Peter J.;
Markl, Michael;
Pandolfino, John E.;
Patankar, Neelesh A.;
Theoretical and Applied Mechanics Program , McCormick School of Engineering , Northwestern University , Evanston , IL , United States;
Department of Radiology , Feinberg School of Medicine , Northwestern University , Chicago , IL , United States;
Department of Mechanical Engineering , McCormick School of Engineering , Northwestern University , Evanston , IL , United States;
Department of Medicine , Feinberg School of Medicine , Division of Gastroenterology and Hepatology , Northwestern University , Chicago , IL , United States;
Department of Mechanical Engineering , McCormick School of Engineering , Northwestern University , Evanston , IL , United States;
Department of Medicine , Feinberg School of Medicine , Division of Gastroenterology and Hepatology , Northwestern University , Chicago , IL , United States
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- Aortic stenosis exacerbates flow aberrations related to the bicuspid aortic valve fusion pattern and the aortopathy phenotype
- Shan, Yan; Li, Jun; Wang, Yongshi; Wu, Boting; Barker, Alex J; Markl, Michael; Wang, Chunsheng; Wang, Xiaolin; Shu, Xianhong; Shanghai Institute of Medical Imaging, Zhongshan Hospital Fudan University, Shanghai, China; Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Zhongshan Hospital Fudan University, Shanghai, China; Department of Transfusion, Zhongshan Hospital Fudan University, Shanghai, China; Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA; Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Zhongshan Hospital Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Zhongshan Hospital Fudan University, Shanghai, China; (European journal of cardio-thoracic surgery : official journal of the European Association for Cardio-thoracic Surgery, v.55, 2019, pp.534-542)
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- Left ventricular flow dynamics and energetics as hemodynamic markers for the assessment of myocardial response to bicuspid aortic stenosis
- Wang, Yongshi; Shan, Yan; Li, Jun; Wu, Boting; Lu, Feiwei; Pan, Yijun; Barker, Alex; Markl, Michael; Lin, Jiang; Shu, Xianhong; ; (Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance, v.27, 2025, pp.101338)
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- Aortic shear stress in patients with bicuspid aortic valve with stenosis and insufficiency
- Shan, Yan; Li, Jun; Wang, Yongshi; Wu, Boting; Barker, Alex J.; Markl, Michael; Wang, Chunsheng; Wang, Xiaolin; Shu, Xianhong; Shanghai Institute of Medical Imaging, Zhongshan Hospital Fudan University, Shanghai, China; Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Zhongshan Hospital Fudan University, Shanghai, China; Department of Transfusion, Zhongshan Hospital Fudan University, Shanghai, China; Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Ill; Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Ill; Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Zhongshan Hospital Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Zhongshan Hospital Fudan University, Shanghai, China; (The Journal of thoracic and cardiovascular surgery, v.153, 2017, pp.1263-1272.e1)
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- Erratum for: CMRxRecon2024: A Multimodality, Multiview k-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRI
- Wang, Zi; Wang, Fanwen; Qin, Chen; Lyu, Jun; Ouyang, Cheng; Wang, Shuo; Li, Yan; Yu, Mengyao; Zhang, Haoyu; Guo, Kunyuan; Shi, Zhang; Li, Qirong; Xu, Ziqiang; Zhang, Yajing; Li, Hao; Hua, Sha; Chen, Binghua; Sun, Longyu; Sun, Mengting; Li, Qing; Chu, Ying-Hua; Bai, Wenjia; Qin, Jing; Zhuang, Xiahai; Prieto, Claudia; Young, Alistair; Markl, Michael; Wang, He; Wu, Lian-Ming; Yang, Guang; Qu, Xiaobo; Wang, Chengyan; ; (Radiology. Artificial intelligence, v.7, 2025, pp.e259001)
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- CMRxRecon2024: A Multimodality, Multiview k-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRI
- Zi Wang; Fanwen Wang; Chen Qin; Jun Lyu; Ouyang Cheng; Shuo Wang; Yan Li; Mengyao Yu; Haoyu Zhang; Kunyuan Guo; Zhang Shi; Qirong Li; Ziqiang Xu; Yajing Zhang; Hao Li; Sha Hua; Binghua Chen; Longyu Sun; Mengting Sun; Qin Li; Ying-Hua Chu; Wenjia Bai; Jing Qin; Xiahai Zhuang; Claudia Prieto; Alistair Young; Michael Markl; He Wang; Lian-Ming Wu; Guang Yang; Department of Bioengineering and Imperial-X, Imperial College London, London, United Kingdom; Cardiovascular Research Centre, Royal Brompton Hospital, London, United Kingdom; Department of Electrical and Electronic Engineering & Imperial-X, Imperial College London, London, United Kingdom; Psychiatry Neuroimaging Laboratory, Brigham and Women’s Hospital, Harvard Medical School, Boston, Mass; Department of Computing & Department of Brain Sciences, Imperial College London, London, United Kingdom; Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China; Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Human Phenome Institute, Fudan University, Shanghai, China; Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China; Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China; Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China; Human Phenome Institute, Fudan University, Shanghai, China; School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China; GE Healthcare, Beijing, China; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Department of Cardiovascular Medicine, Ruijin Hospital Lu Wan Branch, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Human Phenome Institute, Fudan University, Shanghai, China; Human Phenome Institute, Fudan University, Shanghai, China; Human Phenome Institute, Fudan University, Shanghai, China; Siemens Healthineers Ltd, Shanghai, China; Department of Computing & Department of Brain Sciences, Imperial College London, London, United Kingdom; School of Nursing, The Hong Kong Polytechnic University, Hong Kong, China; School of Data Science, Fudan University, Shanghai, China; Millenium Institute for Intelligent Health care Engineering, Santiago, Chile; School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom; Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, Ill; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China; Department of Radiology, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; School of Biomedical Engineering and Imaging Sciences, King’s College London, London, United Kingdom; (Radiology: Artificial Intelligence, v., 2025, )
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- CMRxRecon2024: A Multimodality, Multiview k-Space Dataset Boosting Universal Machine Learning for Accelerated Cardiac MRI
- Wang, Zi; Wang, Fanwen; Qin, Chen; Lyu, Jun; Ouyang, Cheng; Wang, Shuo; Li, Yan; Yu, Mengyao; Zhang, Haoyu; Guo, Kunyuan; Shi, Zhang; Li, Qirong; Xu, Ziqiang; Zhang, Yajing; Li, Hao; Hua, Sha; Chen, Binghua; Sun, Longyu; Sun, Mengting; Li, Qing; Chu, Ying-Hua; Bai, Wenjia; Qin, Jing; Zhuang, Xiahai; Prieto, Claudia; Young, Alistair; Markl, Michael; Wang, He; Wu, Lian-Ming; Yang, Guang; Qu, Xiaobo; Wang, Chengyan; Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, China; Department of Bioengineering and Imperial-X, Imperial College London, London, United Kingdom; Department of Electrical and Electronic Engineering & Imperial-X, Imperial College London, London, United Kingdom; School of Computer and Control Engineering, Yantai University, Yantai, China; Department of Computing & Department of Brain Sciences, Imperial College London, London, United Kingdom; Digital Medical Research Center, School of Basic Medical Sciences, Fudan University, Shanghai, China; Department of Radiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Human Phenome Institute, Fudan University, Shanghai, China; Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, National Institute for Data Scien; (Radiology. Artificial intelligence, v.7, 2025, pp.e240443)
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