Aims to assists users in spotting and displaying electrodes in patients treated with deep brain stimulation (DBS). Lead-DBS is a program that gathers tools facilitating DBS electrode reconstructions and related processing. This toolkit works by using 3D visualization mode and electrode reconstruction algorithms. It includes the following features: (1) reconstruction of the electrode trajectories; (2) manual correction of the electrode localization; or (3) visualization of a 3D model showing DBS electrodes and their target areas.
Hosts a Simulated Brain Database (SBD) and allows users to run custom MRI simulations with any of several pulse sequences and source digital phantoms, and arbitrary values of the acquisition artifacts. BrainWeb database contains a set of realistic magnetic resonance imaging (MRI) data volumes produced by an MRI simulator. These data can be used by the neuroimaging community to evaluate the performance of various image analysis methods in a setting where the truth is known. The SBD contains simulated brain MRI data based on two anatomical models: normal and multiple sclerosis (MS). For both of these, full 3-dimensional data volumes have been simulated using three sequences (T1-, T2-, and proton-density- (PD-) weighted) and a variety of slice thicknesses, noise levels, and levels of intensity non-uniformity. These data are available for viewing in three orthogonal views (transversal, sagittal, and coronal), and for downloading.
Allows users to perform image-based hemodynamics simulation. SimVascular is an open source software which provides a pipeline from model construction to simulation analysis. The software authorizes image processing, segmentation, meshing, as well as an interactive displaying of the results including point cloud visualization and volume rendering. It can be useful for cardiovascular basic science and clinical research and bioengineering education.
A software framework to create 3D finite element models of the left ventricle from cardiac ultrasound or magnetic resonance imaging (MRI) data. The framework is hardware vendor independent and uses speckle tracking (endocardial border detection) on ultrasound imaging data in the form of DICOM. Standard American Heart Association segment-based strain analysis can be performed using a browser-based interface. The speckle tracking, border detection and model fitting methods are implemented in C++ using open-source tools. They are wrapped as web services and orchestrated via a JBOSS-based application server.
Allows to create a high-quality, matched template for a pediatric sample, based on the statistical analysis of a large, healthy pediatric reference population. The Template-O-Matic Toolbox has been updated to run in SPM8. It allows the user to generate customized priors for "classical" unified segmentation (GM, WM, CSF, and T1) as well as for "new segment" (GM, WM, CSF, T1 plus 3 non-brain tissue classes in a single .nii-file). This version also includes an integrated update algorithm that allows easy access to possible updates and fixes.
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