Deep brain stimulation (DBS) surgery, a type of microelectrode-guided surgery, is an effective treatment for the movement disorders patients that can no longer be treated by medications. New rigid and non-rigid image registration methods were developed for the movement disorders patients that underwent DBS surgery. These new methods help study and analyze the brain shift during the DBS surgery and perform atlas-based segmentation of the deep brain structures for the DBS surgery planning and navigation. A diploë based rigid registration method for the intra-operative brain shift analysis during the DBS surgery was developed. The proposed method for the brain shift analysis ensures rigid registration based on diploë only, which can be treated as a rigid structure as opposed to the brain tissues. The results show that the brain shift during the DBS surgery is comparable to the size of the DBS targets and should not be neglected. This brain shift may further lengthen and complicate the DBS surgery contrary to the common belief that brain shift during the DBS surgery is not considerable. We also developed an integrated electrophysiological and anatomical atlas with eleven deep brain structures segmented by an expert, and electrophysiological data of four implant locations obtained from post-op MRI data of twenty patients that underwent DBS surgery. This atlas MR image is then non-rigidly registered with the pre-operative patient MR image, which provides initial DBS target location along with the segmented deep brain structures that can be used for guidance during the microelectrode mapping of the stereotactic procedure. The atlas based approach predicts the target automatically as opposed to the manual selection currently used. The results showed that 85% of the times, this automatic selection of the target location was closer to the target when compared to currently used technique.
| Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/26546 |
| Date | 05 November 2008 |
| Creators | Khan, Muhammad Faisal |
| Publisher | Georgia Institute of Technology |
| Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
| Detected Language | English |
| Type | Dissertation |
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