DTI Helps to Predict Parkinson’s Patient’s Symptoms Using Data Mining Techniques
Deep Brain Stimulation (DBS) is commonly used to treat, inter alia, movement disorder symptoms in patients with Parkinson’s disease, dystonia or essential tremor. The procedure stimulates a targeted region of the brain through implanted leads that are powered by a device called an implantable pulse...
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Published in | Intelligent Information and Database Systems Vol. 11432; pp. 615 - 623 |
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Main Authors | , , , |
Format | Book Chapter |
Language | English |
Published |
Switzerland
Springer International Publishing AG
2019
Springer International Publishing |
Series | Lecture Notes in Computer Science |
Subjects | |
Online Access | Get full text |
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Summary: | Deep Brain Stimulation (DBS) is commonly used to treat, inter alia, movement disorder symptoms in patients with Parkinson’s disease, dystonia or essential tremor. The procedure stimulates a targeted region of the brain through implanted leads that are powered by a device called an implantable pulse generator (IPG). The mentioned targeted region is mainly chosen to be subthalamic nucleus (STN) during most of the operations. STN is a nucleus in the midbrain with a size of 3 mm × 5 mm × 9 mm that consist of parts with different physiological functions. The purpose of the study was to predict Parkinson’s patient’s symptoms defined by Unified Parkinson’s Disease Rating Scale (UPDRS) that may occur after the DBS treatment. Parameters had been obtained from 3DSlicer (Harvard Medical School, Boston, MA), which allowed us to track connections between the stimulated part of STN and the cortex based on the DTI (diffusion tensor imaging). |
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ISBN: | 9783030148010 3030148017 |
ISSN: | 0302-9743 1611-3349 |
DOI: | 10.1007/978-3-030-14802-7_53 |