3-D brain segmentation towards the integration of DTI and MRI modalities.

This study introduces a 3-D segmentation method together with a graphical user interface (GUI) as means to effectively automate the process of segmentation with the ultimate objective of integrating and visualizing diffusion tensor imaging (DTI) with magnetic resonance imaging (MRI) in a fully automated 3-D brain imaging system. A secondary objective is to reduce significantly the segmentation time required to extract key landmarks of the brain in contrast to the manual process currently used at many hospital settings. The results provided will prove this important assertion.

Detection of interictal spikes and artifactual data through orthogonal transformations.

This study introduces an integrated algorithm based on the Walsh transform to detect interictal spikes and artifactual data in epileptic patients using recorded EEG data. The algorithm proposes a unique mathematical use of Walsh-transformed EEG signals to identify those criteria that best define the morphologic characteristics of interictal spikes. EEG recordings were accomplished using the 10-20 system interfaced with the Electrical Source Imaging System with 256 channels (ESI-256) for enhanced preprocessing and on-line monitoring and visualization.

A new mathematical approach based on orthogonal operators for the detection of interictal spikes in epileptogenic data.

This study focuses on the design of orthogonal operators based on unique Electroencephalograph (EEG) signal decompositions in order to detect interictal spikes that characterize epileptic seizures in EEG data. The merits of the algorithm are: (a) in elaborating a unique analysis scheme that scrutinizes EEG data through orthogonal operators designed to extract features that best characterize spikes in epileptogenic EEG data; and (b) in establishing mathematical derivations that provide quantitative measures through the designed operators, and characterize and locate the event of an interictal spike. The uniqueness of this algorithm is in its good performance and simplicity of implementation.

Interictal spike detection using the Walsh transform.

The objective of this study was to evaluate the feasibility of using the Walsh transformation to detect interictal spikes in electroencephalogram (EEG) data. Walsh operators were designed to formulate characteristics drawn from experimental observation, as provided by medical experts. The merits of the algorithm are: 1) in decorrelating the data to form an orthogonal basis and 2) simplicity of implementation.