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Pairwise learning for medical image segmentation
Affiliation:1. School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, 710049, China;2. Jarvis Lab, Tencent, Shenzhen, 518075, China;1. Department of Neurosurgery, University of California, Los Angeles, United States;2. Department of Radiology, University of California, Los Angeles, United States;1. College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China, 518060;2. National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Health Science Center, Shenzhen University, Shenzhen, China, 518060;1. Dermatology Service, Memorial Sloan Kettering Cancer Center, New York, 11377,NY, USA;2. Electrical and Computer Engineering Department, Northeastern University, Boston, 02115, MA, USA;3. Caliber Imaging and Diagnostics, Rochester, Rochester, 14623, NY, USA;4. Department of Pathology at SUNY Downstate Medical Center, New York, 11203, NY, USA;5. SkinMedical Research Diagnostics, P.L.L.C., Dobbs Ferry, 10522, NY, USA;6. University of Modena and Reggio Emilia, Reggio Emilia, Italy;1. Tencent Jarvis Lab, Shenzhen, China;2. Diagnosis and Treatment for Cervical Lesions Center, Shenzhen Maternity & Child Healthcare Hospital, Shenzhen, China;3. Department of Epidemiology and Biostatistics, School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China;4. Tencent Health, Shenzhen, China;1. IBM Zurich Research Lab, Zurich, Switzerland;2. Computer-Assisted Applications in Medicine, ETH Zurich, Zurich, Switzerland;1. Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu 610065, PR China;2. Department of Radiation Oncology, West China Hospital, Sichuan University, Chengdu 610041, PR China
Abstract:
Keywords:
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