AHM2009:UNC

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UNC Roadmap Project

Brain development

Cortical thickness on WM surface

Overview

• What problem does the pipeline solve, and who is the targeted user?

There is a lack of appropriate tools for processing of pediatric MRI, a challenging topic since pediatric MRI differs significantly from adult MRI due to variable brain shape and the process of maturation/myelination which are reflected in nonlinear shape/volume changes but also regional change of white matter....

We would like to create an end-to-end application within Slicer3 allowing individual and group analysis of regional and local cortical thickness. Such a workflow applied to the young brain (2-4 years old) is one goal of the UNC DBP

• How does the pipeline compare to state of the art

A statistical analysis is currently performed in order to compare our pipeline with FreeSurfer. We use a pediatric dataset of 90 cases including controls autistic children and developmental-delays, 2 groups being considered: 2 year-old cases and 4-year old cases.

Detailed Information about the Pipeline

• Illustrate the components and workflow of the pipeline using your own data
• Demonstrate parameters/steps that need to be adjusted using someone else's data

• Regional cortical thickness pipeline

• Local cortical thickness pipeline

Software & documentation

• Executables and tutorial dataset: http://www.nitrc.org/projects/arctic/
• Pediatric atlases: http://insight-journal.org/midas/collection/view/34

Team

• DBP: University of North Carolina at Chapel Hill
  • Co-PI: Heather Cody Hazlett, PhD
  • Co-PI: Joseph Piven, MD
  • UNC DBP: Clement Vachet
• Core 1: Martin Styner, UNC Chapel Hill
  • UNC Algorithm: Ipek Oguz, Nicolas Augier, Marcel Prastawa, Marc Niethammer, Cedric Mathieu, Clement Vachet
• Core 2: Jim Miller, GE Research
• Contact: Heather Cody Hazlett, PhD, (heather_cody at med.unc.edu, Ph: 919-966-4099)

Outreach

• Publication Links to the PubDB.
• Planned outreach activities (including presentations, tutorials/workshops) at conferences