In the NIST lab we develop computer vision image processing algorithms for analysis of medical images that are focused on registration and segmentation. These techniques are applied to different research projects that include:
  • image guided neurosurgery
  • disease diagnosis, and
  • prognosis and quantification for diseases such as multiple sclerosis, epilepsy, schizophrenia and degenerative diseases such as Alzheimer’s dementia.

Better late than never… Congratulations to Josh Bierbrier, a @bbme_mcgill student working on measuring uncertainty in patient-image registration for image-guided neurosurgery, for obtaining an @HBHLMcGill masters fellowship in July this year.

Congratulations to Daniel DiGiovanni, @IPNMcGill PhD student in the NIST lab on receiving the well-deserved Harold and Audrey Fisher Brain Tumour Award from the Faculty of Medicine @McGillU for his research on brain connectivity and brain tumours.

Looking for stereotaxic registration templates for FTD and its variants? Great work by the team of @anitamanera @vfonov @DadarMahsa and @sducharme66 to generate the MNI-FTD templates with paper at https://rdcu.be/cv0dN and templates at http://nist.mni.mcgill.ca/mni-ftd-templates/

Mahsa Dadar@DadarMahsa

MNI-FTD templates, unbiased average templates of frontotemporal dementia variants https://rdcu.be/cv0dN @anitamanera @vfonov @sducharme66 @dlouiscollins @AlzCanada

Congrats to Pulkit Khandelwal for his paper using using geometric flows and shape priors to segment the spine and individual vertebrae from CT images. From a great ongoing collaboration with Kaleem Siddiqi. https://www.frontiersin.org/articles/10.3389/fcomp.2021.592296/full

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