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.

Hi all. group-specific templates can help to be more representative. We’ve created MRI templates for paediatric data using data from the NIHPD project, as well as disease-specific templates for PD and FTD (and will soon AD). These are all available at http://nist.mni.mcgill.ca/atlases/

Jonathan Peelle@jpeelle

I feel like I should know this, but don’t. Are there alternative brain atlases (existing or in development) that might reflect a more representative sample than MNI152? e.g. age, race, etc.

Dr. Cassandra Morrison (@CassMorrison01) has been awarded an RBIQ @rbiq_qbin recruitment award for her PDF in the @NistLab of the @bic_mni in @TheNeuro_MNI to study cognitive and MRI biomarkers in subjective cognitive decline. Congratulations!!

Congratulations to #BBME_McGill PhD candidate Daniel Andrews on winning the 2021 @CIHR_IRSC IA’s Anne Martin-Matthews Prize of Excellence in Research on Aging, recognizing the top doctoral trainee in the field of aging. Wow! @TheNeuro_MNI @NistLab

Great paper from postdoc Dr. Cassandra Morrison and team showing WMH associated with ⬇️ 2y follow-up exec function and general cognition, while pTau was not associated with cognitive decline. ⬇️ Aß42/40 associated only with ⬇️ exec function at baseline in ADNI NCs. @NISTlab

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