Rough Set Rules Help to Optimize Parameters of Deep Brain Stimulation in Parkinson’s Patients
Deep brain stimulation (DBS) is a well established method used as treatment in patients with advanced Parkinson’s disease (PD). Our main purpose is to increase precision of DBS method by determining which parts of cortex are stimulated in different set-ups. In this paper we have analyzed MRIs that are performed as a standard procedure before and after the DBS surgery. We have used 3D Slicer for registration of MRIs with anatomical brain atlas. In addition, we have generated trajectories of neural tracts (tractography) connecting STN with cortex using data colected by DTI (Diffusion Tensor Imaging). In the following step we have used Rougt Set Theory to compare MRI data with neurological findings acquired by neurologists. We have tested prediction of DBS electrode contact’s position and stimulating parameters in individual patients on improvements of particular neurological symptoms. Our results may give a basis to set optimal parameters of stimulation and electrode’s position in order to obtain the most effective PD treatment.
KeywordsDeep Brain Stimulation Parkinson’s disease 3D image analysis RSES MRI DTI
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