![]() ![]() The reliability analysis showed that shape descriptors achieved moderate to good test-retest reliability. Here we used shape analysis to derive length, area, volume, and shape metrics from diffusion MRI tractography and utilized them to study the morphology of human association pathways. Shape analysis has been widely used in digital image processing and computer vision, but they have not been utilized to compare the structural characteristics of the human association pathways. Further analysis is needed to confirm these findings which may have clinical importance. Additional optimizations of N-localizer geometry may also reduce potential targeting errors. Keeping the target point within the stereotactic triangle enclosed by the diagonal rods can also reduce errors. The application of vertical rod positions enhances computational accuracy and can be performed on any N-localizer system. Root Mean Square Errors (RMS-e) computed via millions of MC iterations for each study demonstrated that errors were reduced by (1) inclusion of the x- and y-coordinates of the vertically oriented rods, (2) a greater triangular area enclosed by the diagonal fiducials of the N-localizer system (stereotactic triangle), (3) a larger W/H ratio, and (4) an N-localizer system that comprised four N-localizers.Ĭonclusion: Monte Carlo simulations of Root Mean Square Error (RMS-e) is a useful technique to understand targeting while using N-localizer systems in stereotactic neurosurgery. Results: The inclusion of an overdetermined system of equations and the geometries of the N-localizer systems had significant effects on target errors. Errors were computed using the MC simulations that included the x- and y-axes of vertically oriented rods, that altered the W/H ratio, and that added a fourth N-localizer to a three N-localizer system. The simulations included native and altered geometric dimensions (Width x Height ). Methods: N-localizer systems comprising three and four N-localizers of various geometries were analyzed using Monte Carlo (MC) simulations. We highlight these potential errors and develop methods to reduce them. Analysis of targeting errors related to the N-localizer has not been carried out in sufficient detail. The N-localizer is an integral component of most of the extant systems. Introduction: Frame-based stereotaxis has been widely utilized for precise neurosurgical procedures throughout the world for nearly 40 years. However, there is a lack of standard validation metrics, which makes the performance measurement difficult when external objects are presented, caused primarily by the absence of a gold-standard dataset for comparison. ![]() The literature review found that rigid registration was the most used technique when electrode localization in SEEG is required, which was the proposed method in nine of the found articles. ![]() The search was conducted using the databases and search engines of Scopus, IEEE, PubMed, Springer, and Google Scholar, resulting in 15 primary source articles. In this paper, a literature review is presented, applying the methodology proposed by Kitchenham to determine the main techniques of multi-modal brain image fusion, the most relevant performance metrics, and the main fusion tools. Moreover, it is essential to know how to measure the performance of fusion methods in the presence of external objects, such as electrodes. The detection relies on invasive diagnostic techniques such as Stereotactic Electroencephalography (SEEG), which uses multi-modal fusion to aid localizing electrodes, using pre-surgical magnetic resonance and intra-surgical computer tomography as the input images. The surgical intervention depends on the correct detection of epileptogenic zones. Resection of the epileptogenic tissue may be needed in approximately 25% of all cases due to ineffective treatment with anti-epileptic drugs. Epilepsy is a common neurological disease characterized by spontaneous recurrent seizures. ![]()
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