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.

As Dr. Feindel was a great mentor to me, it was a great honour to be nominated to give the William Feindel Lecture at the 2022 @rbiq_qbin conference in June.
the talk:
the interview:
@TheNeuro_MNI @bic_mni @McGillBME @NistLab

QC of individual image processing steps is key to accurate neuroimaging results, but manual QC is very time consuming. The publicly available DARQ tool automates QC of the ubiquitous stereotaxic registration step.
@VFonov @DadarMahsa @TheNeuro_MNI @NistLab #OpenScience

Vladimir S. FONOV @vfonov

DARQ paper is out!

Need to do lots of visual QC efficiently? Can u generate images that enable/facilitate the QC decision? My student Sofia Fernandez @soffiafdz is presenting QRater, an open-source, web-based tool for collaborative QC at poster WTh895 #OHBM2022 #OpenScience @TheNeuro_MNI @NistLab

Sophia with an F @soffiafdz

Need to do visual QC on thousands of MRI? My lab did so I developed an application for doing it as quick and easy as possible.

It’s available for download on

Come check it out at #OHBM22 on poster WTh895.

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