DBP2:Harvard:Brain Segmentation Roadmap

Roadmap

The main goal of this application is to characterize anatomical abnormalities in the brain of patients with velocardiofacial syndrome (VCFS), and to link this information with deficits in schizophrenia.

This page describes the technology roadmap for brain automatic segmentation, using newly acquired 3T data, NAMIC tools and slicer 3.

A - Optimization of slicer EM white/gray/csf segmentation 

• We have been using EM segmenter for our 1.5 Tesla data. This protocol needs to be optimizes for 3T data, adjusting for higher data resolution, different intensity profiles and bias field inhomogeneity. This protocol will be in Slicer 3 (Sylvain, Brad)
  • Since technology needed for this project already exists in Slicer 2, its implementation in Slicer 3 is a low risk project, and will be accomplished within the next couple of months.
• Since the EP segmentation uses brain atlas, we need to have the technology in place to generate new templates automatically. (Sylavin, Brad, Paulina)
  • This technology should be developed in relatively short period of time. The fact that segmentation atlases will be generated for each studied, will ultimately make the technology more robust to other brain diseases.

B – Segmentation performance comparison, and validation 

• In order to make sure there is no systematic bias between segmentation results of newly acquired 3T data and old 1.5T data, we have chosen 15 control subjects and 15 schizophrenia subjects, which have both scans. We will run and compare results of segmentation, both between methods and within methods between groups.
  • Since the scanning protocol was established and tested on schizophrenia subjects, and thus data collection is much more advanced there, and since the ultimate goal is to compare anatomical abnormalities in VCFS with these in schizophrenia, this project has two benefits- it gives schizophrenia comparison data, as well as leads to establishing the segmentation protocol that will be easily applicable to VCFS, once more data is collected.

C - Analysis of small anatomical structures 

• After the protocol for whole brain segmentation is established, small anatomical structures, such as STG, hippocampus, cingulate gyrus, thalamus, caudate and dorsolateral prefrontal cortex will be segmented in both schizophrenia (first) and VCFS (later) (Sylvain, Brad).
  • Technology for segmentation of most of these regions is already in place in Slicer 2 (Sylvain, Killian). DLPFC module is especially interesting for VCFS population, and this is the first module that will be optimized for our project.
  • This module is currently being implemented into Slicer2 (John, Brad)
• Using segmented DLPFC ROIs, we will perform cortical thickness analysis (Marc, Sylvain)
  • Marc Niethammer was developed a cortical thickness algorithm, which will be put in Slicer 3 technique

D - Subject comparison 

• Local analysis requires techniques which are not currently in the NA-MIC Kit
  • Freesurfer could be used for the local analysis (but it is not in the NA-MIC Kit)
  • Ipek is developing local analysis tools and may have a tool available in Fall 2008.

To do

• Assign owners to tasks
• Define schedule

Staffing Plan

• Clement is the DBP resource charged with adapting the tools in the NA-MIC Kit to the DBP needs
• Martin is the algorithm core contact
• Jim is the engineering core contact

Schedule

• xx/xx/2007 - White matter/gray matter segmentation of the young brain using UNC technique as a Slicer3 module
• xx/xx/2007 - White matter/gray matter segmentation of the young brain using the Slicer3 EM Segment module
• xx/xx/2007 - Cortical thickness measurement using UNC technique as a Slicer3 module
• xx/xx/2007 - Cortical thickness measurement using Marc Niethammer's approach as a Slicer3 module
• xx/xx/2007 - Deformable registration of young brain regional atlas
• xx/xx/2007 - Regional analysis of cortical thickness as a Slicer3 module
• xx/xx/2007 - BatchMake workflow
• xx/xx/2007 - Groupwise regional analysis of cortical thickness as a NA-MIC Workflow
• xx/xx/200x - Groupwise local analysis of cortical thickness as a NA-MIC Workflow

Team and Institute

• Co-PI: Heather Cody Hazlett, PhD, (heather_cody at med.unc.edu, Ph: 919-966-4099)
• Co-PI: Joseph Piven, MD
• NA-MIC Engineering Contact: Jim Miller, GE Research
• NA-MIC Algorithms Contact: Martin Styner, UNC