2011 Summer Project Week long shape regression

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Longitudinal Shape Regression - Huntington's Disease

Key Investigators

  • Utah: James Fishbaugh, Marcel Prastawa, Guido Gerig
  • Iowa: Hans Johnson


Objective

To begin processing longitudinal Huntington's disease data and to apply our shape regression framework to available data. We are interested in the evolution of sub-cortical structures in the brain.

We would like to estimate continuous growth scenarios for several shapes of interest, which can eventually be combined with a framework for 4D registration or 4D atlas construction, to statistically analyze the growth variability within a population.

Approach, Plan

  • Segment sub-cortical structures
  • Estimate growth trajectories

Progress

Segmentation

The 6 pairs of sub-cortical structures (amygdala, caudate, hippocampus, globus pallidus, putamen, lateral ventricle) were segmented using a deformable atlas based pipeline used at the University of Utah. The quality of the ventricles was very poor, so they were further improved by an active contour based segmentation tool, itkSNAP. After this stage, we have 12 shapes at 3 time points.

Preprocessing

In order to prepare the shapes for longitudinal regression, the different time points must first be rigidly aligned.


Snapshots of the evolution of several sub-cortical structures. Click here for an animation.
Volume measured after shape regression. Plus signs denote target volume.

References

Fishbaugh, J., Durrleman, S., Gerig, G. "Estimation of Smooth Growth Trajectories With Controlled Acceleration From Time Series Shape Data". MICCAI 2011. To appear.