Makeig-Worrell

NCRR

Project OverviewScott Makeig, Ph.D. is the Director of the Swartz Center for Computational Neuroscience Institute for Neural Computation at UCSD

Greg Worrell, M.D., Ph.D. is a neurologist at the Mayo Clinic.

Goal: EEG Source Localization and Multimodality Imaging for Epilepsy Surgery

The Center will provide support for EEG and MEG source reconstruction from model generation (image and geometry processing) through simulation to visualization.

Makeig-Worrell

NCRR

Impact of Center to DatePreliminary Results

Collaboration started in July 2004. - First goal: Case study of an epilepsy patient from the Mayo Clinic with medically intractable epilepsy.

- Utah Center - Image conversion tools- Registration of CT and the T1-MR datasets- Segmented datasets into 4 tissue classes using ITK within BioPSE.

- ICA decompositions of combined sEEG and iEEG data - Localization of peri-ictal dipolar ICA map using the Neuro-FEM linked to BioPSE

- Visualized segmentation, head models, and simulation results using BioPSE

Makeig-Worrell

NCRR

Impact of Center in the FutureUpcoming Plans and Timeline: - Combine EEG and MEG data comparing the extent volume conductor properties can account for source reconstruction differences between EEG and MEG and if the combination EEG/MEG and the computation in a realistic high-resolution anisotropic volume conductor model can improve the ICA-based localization.

- Measure and exploit DT-MRI for white matter modeling within our simulations.

- Test our ideas on a statistically significant number of appropriate epilepsy patients from the Mayo clinic.

Makeig-Worrell

NCRR

ModelCreation Pipeline

Segmentation toolsSegment CT and MRI data:extract Scalp, Skull, CSF, Grey matter,white matter

Mesh generation toolsCreate a mesh (hexahedral or tetrahedral) from the segmented data set.

Use finite elements to generate leadfield

Create a leadfield from the volume of interest to the electrodes

Makeig-Worrell

NCRR

Segmentation ToolsSegmentation tools:• Developed a new tool to do segmentation in.• Implemented Confidence Connected algorithm• Implemented Levelset Segmentation

Makeig-Worrell

NCRR

Mesh Creation ToolsGenerating a hexahedral mesh:• Upgraded core SCIRun functionality to work with hexahedral meshes

• Implemented hexahedral resampling and hexahedral refinement

• Implemented tools for selecting nodes to serve as electrodes.

Generating a tetrahedral mesh:• Experimenting with surface extraction and resampling.

• Integrated TetGen as Tetrahedral mesh generator

Makeig-Worrell

NCRR

Finite Element ToolsModel generation:• Implemented hexahedral finite elements(implemented for each mesh type)

• Implemented gradient, current density for hexahedral elements.• Implemented boundary conditions for hexahedral elements.• Fixed problems with SCIRun solver

Makeig-Worrell

NCRR

Segmentation results

CSFWhite matterGrey matter

Segmentation of the brain using an statistical approach using brain atlases .

Makeig-Worrell

NCRR

Visualization resultsVolume rendering using segmentation as index into theshader that is used.

Different tissues are renderedwith different transfer functions.

Makeig-Worrell

NCRR

Short Term Goals

Fix gaps in MR/CT image to model pipeline:

• Implement schemes to segment white/grey matter segmentation

• Investigate which scheme works best for extracting the skull and scalp.

• Fix the electrode current injection methods and implement lead field estimation for hexahedral elements

Makeig-Worrell

NCRR

Short Term Goals

Extend functionality of SCIRun:• Implement magnetic lead fields and FE computation of magnetic fields.

• Implement surface remesher for tetrahedral models.

• Extend the GUI of tetrahedral mesh generator.

• Implement mesh smoother.