Mahsa Dadar


Post-Doctoral Fellow

I am currently a postdoctoral researcher at the Image Processing lab at McGill University. I obtained my B.Sc. and M.Sc. in Electrical Engineering, Control Systems and my Ph.D. in Biomedical Engineering. My current research is focused on vascular causes of dementia in neurodegenerative disease populations (i.e. Alzheimer’s disease, Parkinson’s disease, and frontotemporal dementia). More specifically, I study white matter hyperintensities (which are the major MRI expressions of small vessel disease) and their effect on cognition.

Research Interests:

  • Medical image analysis
  • Machine learning and pattern recognition
  • Modelling, diagnosis, and prognosis


White Matter Hyperintensities

Tissue Classification

DAWM and FWML Seperation

* Equal contribution




Journal Publications:

  1. Dadar, M., Maranzano, J., Ducharme, S., Collins, D. L., & Alzheimer’s Disease Neuroimaging Initiative. (2019). “White Matter in Different Regions Evolve Differently During Progression to Dementia”. Neurobiology of Aging, 76, 71-79.
  2. Dadar M., Zeighami Y., Yau Y., Fereshtehnejad S.M., Maranzano J., Postuma R.B., Dagher A., Collins D.L. (2018), “White Matter Hyperintensities Are Linked to Cognitive Decline in de Novo Parkinson’s Disease Patients”. NeuroImage: Clinical, 20, 892-900.
  3. Dadar, M., Fonov, V. S., Collins, D. L., “Alzheimer’s Disease Neuroimaging Initiative. (2018). A comparison of publicly available linear MRI stereotaxic registration techniques”. NeuroImage, 174, 191-200.
  4. Dadar, M., Maranzano, J., Ducharme, S., Carmichael, O. T., Decarli, C., Collins, D. L., & Alzheimer’s Disease Neuroimaging Initiative. (2018). “Validation of T 1w‐based segmentations of white matter hyperintensity volumes in large‐scale datasets of aging”. Human brain mapping, 39(3), 1093-1107.
  5. Dadar, M., Maranzano, J.,…, Collins, D.L. & Alzheimer’s Disease Neuroimaging Initiative. (2017). “Performance comparison of 10 different classification techniques in segmenting white matter hyperintensities in aging”. NeuroImage, 157, 233-249.
  6.  Dadar, M., Pascoal, T. A., Manitsirikul, S., Misquitta, K., … & Collins, D. L. (2017). “Validation of a regression technique for segmentation of white matter hyperintensities in Alzheimer’s disease”. IEEE transactions on medical imaging, 99, 1-1.
  7. Mateos-Pérez * , Dadar * , M., J. M., Lacalle-Aurioles, M., Iturria-Medina, Y., Zeighami, Y., & Evans, A. C. (2018). “Structural neuroimaging as clinical predictor: a review of machine learning applications”. NeuroImage: Clinical, 20, 506-522.
  8. Misquitta * , K., Dadar * , M., Tarazi, A., Hussain, M. W., Alatwi, M. K., Ebraheem, A., … & Tator, C. (2018). “The relationship between brain atrophy and cognitive-behavioural symptoms in retired Canadian football players with multiple concussions”. NeuroImage: Clinical, 19, 551-558.
  9. Maranzano, J., Dadar, M., Rudko, D. A., De Nigris, D., Elliott, C., Gati, J. S., … & Narayanan, S. (2019). “Comparison of Multiple Sclerosis Cortical Lesion Types Detected by Multicontrast 3T and 7T MRI”. American Journal of Neuroradiology.
  10. Vainik, U., Baker, T. B., Dadar, M., Zeighami, Y., Michaud, A., Zhang, Y., … & Dagher, A. (2018). “Neurobehavioural Correlates of Obesity are Largely Heritable”. PNAS, 115(37):9312-9317.
  11. Sanford, R., Strain, J., Dadar, M., Maranzano, J., Bonnet, A., Mayo, N. E., … & Collins, D. L. (2019). HIV infection and cerebral small vessel disease are independently associated with brain atrophy and cognitive impairment. Aids, 33(7), 1197-1205.
  12. Pandya, S., Zeighami, Y., Freeze, B., Dadar, M., Collins, D. L., Dagher, A., & Raj, A. (2019). “Predictive model of spread of Parkinson’s pathology using network diffusion”. NeuroImage, 192, 178-194.
  13. Neseliler, S., Hu, W., Larcher, K., Zacchia, M., Dadar, M., Scala, S. G., … & Marliss, E. B. (2019). “Neurocognitive and hormonal correlates of voluntary weight loss in humans”. Cell metabolism, 29(1), 39-49.
  14. García-García * , I., Michaud * , A., Dadar, M., Zeighami, Y., Neseliler, S., Collins, … & Dagher, A. (2018). “Neuroanatomical differences in obesity: meta-analytic findings and their validation in an independent dataset”. International Journal of Obesity, 1.
  15. Yau, Y., Zeighami, Y., Baker, T. E., Larcher, K., Vainik, U., Dadar, M., … & Collins, D. L. (2018). “Network connectivity determines cortical thinning in early Parkinson’s disease progression”. Nature communications, 9(1), 12.
  16. Zeighami, Y., Fereshtehnejad, S. M., Dadar, M., Collins, D. L., Postuma, R. B., Mišić, B., & Dagher, A. (2017). “A clinical-anatomical signature of Parkinson’s Disease identified with partial least squares and magnetic resonance imaging”. NeuroImage.
  17. Boucetta, S., Salimi, A., Dadar, M., Jones, B. E., Collins, D. L., & Dang-Vu, T. T. (2016). “Structural brain alterations associated with rapid eye movement sleep behavior disorder in Parkinson’s disease”. Scientific reports, 6, 26782.
  18. Zeighami, Y., Ulla, M., Iturria-Medina, Y., Dadar, M., Zhang, Y., Larcher, K. M. H., … & Dagher, A. (2015). “Network structure of brain atrophy in de novo Parkinson’s disease”. Elife, 4, e08440.
  19. Orban, Pierre, et al. (2015). “Test-retest resting-state fMRI in healthy elderly persons with a family history of Alzheimer’s disease”. Scientific data 2. 150043.
  20. Kuijf, H. J., et al. (2019). “Standardized assessment of automatic segmentation of white matter hyperintensities; results of the wmh segmentation challenge”. IEEE transactions on medical imaging.