Analysis and visualization of brain connectivity

using diffusion tensor MR imaging

Supervisor: Daniel RueckertMembers: Caroline Baroukh,

Rouslan Dimitrov,Przemyslaw Korzeniowski,Danial Sheikh

Introduction

• Multiple MRI scans provide 3D voxel grid

• Changing MRI polarizations yields slightly different results based on tissue orientation

• Diffusion tensor imaging (DTI) exploits this to assign anisotropy tensors to voxels

Introduction

• After processing,

• where:

e - major axis of anisotropy ellipsoidfa - fractional anisotropy [0…1]Pv - voxel center

• Idea: use ellipsoids to trace curves (connecting fibers) in the brain!

),(),,( faezyxV

Pv

e

Outline

• Aim of the project

• Overview of the application

• Tracing algorithm

• GUI

• Demo

• Group organization

Aim of the project

Aim of the project

• Application that interactively traces and visualizes fibers

• Regions of interest (ROIs) used as starting point of fibers

• ROIs loaded from a segmentation file or defined manually

• Provide typical medical imaging visualization (eg. cutting planes, glyphs, etc)

(Technical) Overview of the application

• Application in JAVA

– Developed from scratch

– Various toolboxes + interactive 3D display

• Tracer in C++

– Extends VTK

– 2 new filters:vtkFiberTracer and vtkInterpolatedDifTensors

Tracer

• Input:

– DTI data (eigenvector and fractional anisotropy)

– Fiber Seed points

• Output:

– Fibers as polylines (connected series of line segments).

Tracer

for each seedpoint

f = new fiber polyline;

do

move in direction of anisotropy to P

f.AddPoint(P)

until numberOfSteps exceeded

store f;

Use custom second ordercurvature-preserving integrator

Seed

?

Tracer

for each seedpoint

f = new fiber polyline;

do

move in direction of anisotropy to P

f.AddPoint(P)

if(fractional anisotrpy < fThresh)

break

until numberOfSteps exceeded

store f;

Empirically fThresh = 0.2

Tracer

• MRI provides low resolution scans ~1283

• Need to use steps much smaller than the voxel size

• Use bilinear interpolation from 8 closest voxel centers

• Danger: 3000 fibers * 100 steps * 8 samples * n,where n is the order of the integrator, can be high!

Tracer

• Problem: 30% of the voxels contain at least two different neural tracts traveling in different directions

• Solution:Add inertia to the fiber, so that low anisotropy

regions cannot change its direction

vtkInterpolatedDifTensors

• Problem: Which way to go?

• Anisotropy ellipsoids have no direction!

• Solution:

– Flip vectors on the fly

– This needs sense of direction

– Recover it from previous look-up

• Implemented in vtkInterpolatedDifTensors, inherits interface from vtkInterpolatedVectorField

vtkInterpolatedDifTensors

Tracer

• Parameters exposed in the GUI from the Streamline Panel

• Tracing from anatomical ROIs is done by randomly scattering points within them

• Tracing from a user selected sphere distributes the seeds on the surface

GUI overview & Demo

Questions?