NeuroDebian Virtual Machine Deployment Facilitates Trainee-Driven Bedside Neuroimaging Research

Alexander Cohen, Daniel Kenney-Jung, Hugo Botha, Jan-Mendelt Tillema

Research output: Contribution to journalArticle

Abstract

Freely available software, derived from the past 2 decades of neuroimaging research, is significantly more flexible for research purposes than presently available clinical tools. Here, we describe and demonstrate the utility of rapidly deployable analysis software to facilitate trainee-driven translational neuroimaging research. A recipe and video tutorial were created to guide the creation of a NeuroDebian-based virtual computer that conforms to current neuroimaging research standards and can exist within a HIPAA-compliant system. This allows for retrieval of clinical imaging data, conversion to standard file formats, and rapid visualization and quantification of individual patients' cortical and subcortical anatomy. As an example, we apply this pipeline to a pediatric patient's data to illustrate the advantages of research-derived neuroimaging tools in asking quantitative questions "at the bedside." Our goal is to provide a path of entry for trainees to become familiar with common neuroimaging tools and foster an increased interest in translational research.

Original languageEnglish (US)
Pages (from-to)29-34
Number of pages6
JournalJournal of Child Neurology
Volume32
Issue number1
DOIs
StatePublished - Jan 1 2017

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Keywords

  • cortical localization
  • education
  • epilepsy
  • quantitative MRI
  • translational research
  • virtual machine

ASJC Scopus subject areas

  • Pediatrics, Perinatology, and Child Health
  • Clinical Neurology

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