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Maged Goubran
Maged Goubran, PhD

Scientist

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

Phone: 416-480-6100, ext. 85410

Administrative Assistant: Kimberly Allen
Phone:
416-480-5718
Email:
kimberly.allen@sunnybrook.ca

Education:

  • 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 program focuses on developing novel artificial intelligence (AI) and computational tools to probe, predict, and understand circuit alterations, and model brain pathology in neurological disorders. Dr. Goubran’s research interests combine translational and basic science research. 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, traumatic brain injury and stroke. This work can lead to the identification of novel translational biomarkers and therapeutic targets, advance our understanding of the pathophysiologic mechanisms of circuit disorders, and improve cognitive and functional outcomes through earlier and more personalized treatments and prevention strategies.

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, Zeineh M. Multimodal image registration and connectivity analysis for integration of connectomic data from microscopy to MRI. Nature Communications. 2019;10(1):5504. doi: https://doi.org/10.1038/s41467-019-13374-0
  2. Ottoy J, Ozzoude M, Zukotynski K, Adamo S, Scott C, Gaudet V, Ramirez J, Swardfager W, Cogo-Moreira H, Lam B, Bhan A, Mojiri P, Kang MS, Rabin J, Kiss A, Strother S, Bocti C, Borrie M, Chertkow H, Richard Frayne R, Hsiung R, Laforce RJ, Noseworthy MD, Prato FS, Sahlas DJ, Smith EE, Kuo PH, Sossi V, Thiel A, Soucy J-P, Tardif JC, Black SE*, Goubran M*. The interplay between vascular burden and cognition: The mediating roles of amyloid and neurodegeneration in severe small vessel disease and Alzheimer’s pathology. Alzheimer’s & Dementia. 2022. In-press. doi: https://doi.org/10.1002/alz.12750
  3. Mojiri Forooshani P, Biparva M, Ntiri EE, Ramirez J, Boone L, Holmes MF, Adamo S, Gao F, Ozzoude M, Scott CJM, Dowlatshahi D, Lawrence-Dewar JM, Kwan D, Lang AE, Marcotte K, Leonard C, Rochon E, Heyn C, Bartha R, Strother S, Tardif JC, Symons S, Masellis M, Swartz RH, Moody A, Black SE, Goubran M. Deep Bayesian networks for uncertainty estimation and adversarial resistance of white matter hyperintensity segmentation. Human Brain Mapping. 2022. doi: https://doi.org/10.1002/hbm.25784
  4. 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;228:117692. doi: https://doi.org/10.1016/j.neuroimage.2020.117692
  5. Goubran M, Ntiri EE, Akhavein H, Holmes M, Nestor S, Ramirez J, Adamo S, Ozzoude M, Scott C, Gao F, Martel A, Swardfager W, Masellis M, Swartz R, MacIntosh B, Black SE. Hippocampal segmentation for brains with extensive atrophy using three‐dimensional convolutional neural networks. Human Brain Mapping. 2020;41(2):291-308. doi: https://doi.org/10.1002/hbm.24811

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