School of Medicine
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Postdoctoral Research Fellow, Radiology
Current Research and Scholarly Interests My research focuses on improving acute ischemic stroke care by applying the latest deep learning algorithm on clinical routine imaging and patient clinical data. This includes:
1) more precise prediction of the final stroke lesion from the baseline MR or CT images. This prediction will enable physicians to better select patients for reperfusion therapy.
2) prediction penumbra using non-contrast enhanced MRI.
3) Automatic detection of artery occlusion and mTICI classification on DSA image.
Professor of Radiology (Neuroimaging and Neurointervention)
Current Research and Scholarly Interests Improving medical image quality using deep learning artificial intelligence
Imaging of cerebral hemodynamics with MRI and CT
Noninvasive oxygenation measurement with MRI
Clinical imaging of cerebrovascular disease
Imaging of cervical artery dissection
MR/PET in Neuroradiology
Resting-state fMRI for perfusion imaging and stroke
Associate Professor of Radiology (Neuroimaging and Neurointervention) at the Stanford University Medical Center
Bio Dr. Michael Zeineh received a B.S. in Biology at Caltech in 1995 and obtained his M.D.-Ph.D. from UCLA in 2003. After internship also at UCLA, he went on to radiology residency and neuroradiology fellowship both at Stanford. He has been an assistant professor of radiology since 2010. Combining clinical acumen in neuroradiology with advanced MRI acquisition and image processing as well as histologic validation, Dr. Zeineh hopes to advance the care of patients with neurodegenerative disorders. In particular, he is interested in Alzheimer's disease, sports-related mild traumatic brain injury, and chronic fatigue syndrome. Additionally, he is specifically interested and has over 20 years of experience studying hippocampal anatomy and pathology.