Published on in Vol 8, No 11 (2020): November
Deep Learning Methodology for Differentiating Glioma Recurrence From Radiation Necrosis Using Multimodal Magnetic Resonance Imaging: Algorithm Development and Validation
Deep Learning Methodology for Differentiating Glioma Recurrence From Radiation Necrosis Using Multimodal Magnetic Resonance Imaging: Algorithm Development and Validation
1 Beijing Academy of Quantum Information Sciences , Beijing , CN
2 Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing , CN
3 School of Instrumentation and Optoelectronic Engineering, Beihang University , Beijing , CN
4 Department of Neuropathology, Beijing Neurosurgical Institute, Capital Medical University, Beijing , CN
5 School of Computer Science, The University of Sydney , Sydney , AU
6 Surgical Planning Laboratory, Department of Radiology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, US
7 Department of Computer Science, University of Bremen , Bremen , DE
8 Fraunhofer Institute for Digital Medicine MEVIS , Bremen , DE
9 Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University , Sydney , AU
10 Computational NeuroSurgery Lab, Department of Clinical Medicine, Faculty of Medicine and Health Sciences, Macquarie University, Sydney , AU
*these authors contributed equally