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End-to-end multimodal image registration via reinforcement learning
Institution:1. Department of Computer Science, Chengdu University of Information Technology, P.R. China, 610225;2. CuraCloud Corporation, USA;3. United Imaging Intelligence, USA;4. Department of Computer Science and Engineering at the University at Buffalo, State University of New York, USA;1. Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA;2. Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, Beijing, China;3. Shanghai United Imaging Intelligence Co. Ltd., Shanghai, China;4. Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea;1. Department of Radiology and BRIC, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA;2. Institute for Medical Imaging Technology, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China;3. Department of Brain and Cognitive Engineering, Korea University, Seoul 02841, Republic of Korea;1. Department of Mathematics, National University of Singapore, Singapore;2. Department of Pure Mathematics and Mathematical Statistics, University of Cambridge, UK;3. Department of Applied Mathematics and Theoretical Physics, University of Cambridge, UK;1. Computer Science and Artificial Intelligence Lab, MIT, Cambridge, MA, USA;2. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, HMS, Charlestown, MA, USA;3. School of Electrical and Computer Engineering, Cornell University, Ithaca, NY, USA;4. Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA
Abstract:
Keywords:
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