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Hurvitz Brain Sciences Program

SRI Programs

Maged Goubran
Maged Goubran, PhD


Sunnybrook Health Sciences Centre
2075 Bayview Ave., Room M6 176
Toronto, ON
M4N 3M5

Phone: 416-480-6100, ext. 85410

Administrative Assistant: Kimberly Allen


  • B.MSc., 2010, medical biophysics, Western University, Canada
  • PhD, 2014, biomedical engineering (imaging), Western University, Canada
  • Research scholar, 2015, Montreal Neurological Institute, McGill University, Canada
  • Postdoctoral fellowship, 2017, department of radiology/neuroscience program, Stanford University, U.S.

Appointments and Affiliations:

Research Foci:

  • Computational neuroscience
  • Machine learning/artificial intelligence
  • Histopathology & tissue clearing
  • Brain networks & connectomics
  • Neuromodulation
  • Alzheimer’s disease
  • Stroke
  • Traumatic brain injury

Research Summary:

Dr. Goubran’s research interests combine translational and basic science research. He aims to develop novel computational, machine learning and imaging tools for interrogating brain circuits across resolution scales and modelling brain pathology. He is particularly interested in studying the underlying mechanisms and pathways behind disease progression of neurological and cerebrovascular disorders that involve disruption of neural circuits, including Alzheimer’s disease (AD) and stroke.

As part of his postdoctoral fellowship at Stanford University, Dr. Goubran developed a computational pipeline for investigating connectome dynamics in 3D cleared tissue and MRI in animal models, working with the pioneers of tissue clearing and optogenetics. His tools are being used by many collaborating labs internationally. At Sunnybrook, he has been developing and using artificial intelligence (AI) techniques for improved structural and lesion segmentation in populations with extensive brain atrophy. He is also working on creating diagnostic models of neurogenerative diseases from rich imaging and clinical data to aid in the great challenge of early and accurate diagnosis.

Dr. Goubran’s research focus includes multi-parametric and morphological analysis of the hippocampus and its subregions in AD. He is interested in studying human hippocampal circuit remodelling and developing imaging approaches to help predict hippocampal subregion pathology from in vivo imaging. Understanding how cellular and structural changes occur in the connected regions to the ischemic core in stroke is important for developing targeted therapies. Dr. Goubran is applying advanced diffusion and functional imaging, in combination with computational methods in preclinical models, to investigate the spatiotemporal effects of stroke on remote connected areas. Another line of his research focuses on modelling stroke outcomes with AI, to predict who will have cognitive and motor impairments.

Selected Publications:

See current publications list at PubMed.

  1. Goubran M, Leuze C, Hsueh B, Aswendt M, Ye L, Tian Q, Cheng MY, Crow A, Steinberg GK, McNab JA, Deisseroth K and Zeineh M. Multimodal image registration and connectivity analysis for integration of connectomic data from microscopy to MRI. Nat Commun. 2019 Dec 3;10(1):5504. doi: 10.1038/s41467-019-13374-0. Epub ahead of print.
  2. Goubran M, Ntiri E, Akhavein H, Holmes M, Nestor S, Ramirez J, Adamo S, Gao F, Ozzoude M, Scott C, Martel A, Swardfager W, Masellis M, Swartz R, MacIntosh B and Black SE. Hippocampal segmentation for atrophied brains using three-dimensional convolutional neural networks. Hum Brain Mapp. 2019 Oct 14. doi: 10.1002/hbm.24811. Epub ahead of print.
  3. Parivash S,Goubran M,Rezaii P, Bian W, Boldt B, Do Huy, Douglas D, Wilson E, Mitchell L, Parekh M, Anderson S, Grant G and Zeineh M. Longitudinal changes in hippocampal subfield volume associated with collegiate football. J Neurotrauma. 2019 Jun 17. doi: 10.1089/neu.2018.6357. Epub ahead of print.
  4. Federau C, Goubran M, Rosenberg J, Henderson J, Halpern CH, Santini V, Wintermark M, Butts Pauly K and Ghanouni P. Transcranial MRI-guided high-intensity focused ultrasound for treatment of essential tremor: Definition of an optimal lesion size, socalization, and thermal dose. J Magn Reson Imaging. 2018 Jul;48(1):58–65. doi: 10.1002/jmri.25878. Epub 2017 Oct 27.
  5. Goubran M, Bernhardt B, Cantor-Rivera D, Lau JC, Blinston C, Hammond R, de Ribaupierre S, Burneo J, Mirsattari S, Steven D, Parrent A, Bernasconi A, Bernasconi N, Peters T and Khan AR. In-vivo MRI signatures of hippocampal subfield pathology in intractable epilepsy. Hum Brain Mapp. 2016 Mar;37(3):1103–19. doi: 10.1002/hbm.23090. Epub 2015 Dec 17.
  6. Ntiri E, Holmes M, Forooshani P, Ramirez J, Gao F, Ozzoude M, Adamo S, Scott C, Dowlatshahi D, Lawrence-Dewar J, Kwan D, Lang T, Symons S, Bartha R, Strother S, Tardif J-C, Masellis M, Swartz R, Moody A, Black SE*, Goubran M*. Improved segmentation of the intracranial and ventricular volumes in populations with cerebrovascular lesions and atrophy using 3D CNNs. Neuroinformatics. 2021. doi: 
  7. Leuze C,* Goubran M,* Barakovic M, Aswendt M, Tian Q, Hsueh B, Crow A, Weber E, Steinberg G, Zeineh M, Plowey E, Daducci A, Innocenti G, Thiran JP, Deisseroth K, McNab JA. Comparison of diffusion MRI and CLARITY fiber orientation estimates in both gray and white matter regions of human and primate brain. Neuroimage. 2021. doi: 

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