Automatic Localization of Deep Stimulation Electrodes Using Trajectory-based Segmentation Approach
This work addresses the need for precise electrode localization in DBS neurosurgery for advanced Parkinson's disease patients, but it appears incremental as it builds on existing segmentation methods.
The paper tackles the problem of automatically locating Deep Brain Stimulation (DBS) electrodes in CT images for Parkinson's disease treatment by using a threshold-based segmentation approach with adaptive threshold detection, resulting in high noise tolerance.
Parkinson's disease (PD) is a degenerative condition of the nervous system, which manifests itself primarily as muscle stiffness, hypokinesia, bradykinesia, and tremor. In patients suffering from advanced stages of PD, Deep Brain Stimulation neurosurgery (DBS) is the best alternative to medical treatment, especially when they become tolerant to the drugs. This surgery produces a neuronal activity, a result from electrical stimulation, whose quantification is known as Volume of Tissue Activated (VTA). To locate correctly the VTA in the cerebral volume space, one should be aware exactly the location of the tip of the DBS electrodes, as well as their spatial projection. In this paper, we automatically locate DBS electrodes using a threshold-based medical imaging segmentation methodology, determining the optimal value of this threshold adaptively. The proposed methodology allows the localization of DBS electrodes in Computed Tomography (CT) images, with high noise tolerance, using automatic threshold detection methods.