3D Slicer
3D Slicer (Slicer) is a multi-platform, open source,
integrated
software for visualization and image computing. It is intended for
computer
scientists and clinical researchers.
The software is extremely well featured. It has functionality
for loading, viewing,
analyzing, processing and interacting with biomedical data, for
segmentation, registration and three-dimensional
visualization of multi-modal image data, as well as advanced image
analysis algorithms for diffusion tensor imaging, functional magnetic
resonance imaging and image-guided therapy. Standard image file formats
are supported, and the application integrates interface capabilities to
biomedical research software and image informatics frameworks.
Slicer can be extended at run-time with plug-in modules,
allowing developers and researchers to customise and specialize Slicer
for a specific purpose.
Slicer is used in a variety of medical applications including
neurosurgery, prostate cancer, cardiovascular
disease, autism, multiple sclerosis, systemic lupus
erythematosus, schizophrenia, orthopedic biomechanics, and
COPD.
Slicer is based on VTK, a graphical library that provides a
high-level interface to OpenGL and a pipeline mechanism to connect
graphical filters.
Features include:
- Sophisticated complex visualization capabilities
- Scene snapshots allow capture of all visualization
parameters of a scene
- Extensive support for IGT and diffusion tensor imaging
- Advanced registration / data fusion capabilities
- Comprehensive I/O capabilities
- Reading and writing DICOM images and a variety of other
formats
- Interactive visualization of images, triangulated 3D
surface models, and volume renderings
- Manual editing
- Fusion and co-registering of data using rigid and non-rigid
algorithms
- Automatic segmentation
- Analysis and visualization of diffusion tensor imaging data
- Tracking of devices for image-guided procedures
- Change Tracker tool for quantification of the subtle
changes in pathology
- Volume Rendering
- FetchMI (Fetch Medial Informatics)
- Large set of modules/filters:
- Informatics: FetchMI, QdecModule, QueryAtlas
- Registration:
ACPC Transform, Affine registration, Deformable BSpline registration,
Diffeomorphic Demons Algorithm, Linear registration, Register images,
Rigid registration
- Segmentation: EMSegment Template Builder,
EMSegment Command-line, EMSegment Simple, Gyri Contour Segmentation,
Otsu Threshold Segmentation, Simple region growing
- Statistics: LabelStatistics
- Diffusion: Diffusion Tensor
Estimation, Diffusion Tensor Scalar Measurements, Python Stochastic
Tractography, Resample DTI Volume, Filtering
- Tractography: FibertBundles, FiducialSeeding, Labelmap
Seeding
- IGT: NeuroNav, OepnIGTLink IF, ProstateNav
- Filtering:
GradientAnisotropicFilter, CheckerBoard Filter, Extract Skeleton,
Histogram Matching, Image Label Combine, Otsu Threshold, Python
Gaussian Smoothing, Python Gradient Anisotropic Diffusion, Resample
Scalar Volume, Resample Scalar/Vector/DWI Volume, Threshold Image,
Voting Binary Hole Filling, Zero Crossing Based Edge Detection Filter,
Arithmetic, Denoising, Morphology
- Surface Modules: ClipModel,
ModelIntoLabelVolume, FreesurferSurfaceSectionExtraction, Grayscale
Model Maker, Label Map Smoothing, Model Maker, Python Surface
Connectivity, Python Surface ICP Registration, Python Surface Toolbox
- Batch Processing: EMSegment BatchMake, Gaussian Blur
BatchMake, Register Images BatchMake, Resample Scalar Volume BatchMake
- Converters:
ExtractSubvolume, Create a DICOM Series, Dicom DWI loader, Dicom to
Nrrd, Orient Images, Python Binarize Map, Python Convert Fiducials to
Labelmap, Python Convert Volume to NUMPY File, Python Create Single ROI
file, Python Explode Volume Transform, Python Load Volume from NUMPY
File, Python Resample Volume, Python Reslice As Volume
- Developer Tools: ScriptedModuleExample, Execution Model
Tour, Python Numpy Script, Python Script
- ROI seeding
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Last Updated Sunday, April 01 2012 @ 12:41 PM EDT
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