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Diverse Applications of Artificial Intelligence in Neuroradiology
Michael Tran Duong1, Andreas M Rauschecker2, Suyash Mohan3
1Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, 3400 Spruce Street, 219 Dulles Building, Philadelphia, PA 19104, USA. Electronic address: https://twitter.com/MichaelDuongMD.
Abstract:
Recent advances in artificial intelligence (AI) and deep learning (DL) hold promise to augment neuroimaging diagnosis for patients with brain tumors and stroke. Here, the authors review the diverse landscape of emerging neuroimaging applications of AI, including workflow optimization, lesion segmentation, and precision education. Given the many modalities used in diagnosing neurologic diseases, AI may be deployed to integrate across modalities (MR imaging, computed tomography, PET, electroencephalography, clinical and laboratory findings), facilitate crosstalk among specialists, and potentially improve diagnosis in patients with trauma, multiple sclerosis, epilepsy, and neurodegeneration. Together, there are myriad applications of AI for neuroradiology."
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