Difference between revisions of "Slicer4:VectorImageVisualization"
From Slicer Wiki
| Line 32: | Line 32: | ||
* Multi-component scalar-volume visualization: as with the DWI-images where there is a slider enabling the user to choose which component to visualize | * Multi-component scalar-volume visualization: as with the DWI-images where there is a slider enabling the user to choose which component to visualize | ||
| − | * Glyph-based visualization | + | *Split and merge into individual volumes. Concept is partially implemented in split and merge in the interactive editor |
| − | ** Visualization as vectors (deformation fields, principal diffusion direction) | + | * Visualization of derived values: |
| − | ** Visualization as Ellipsoids or | + | **dMRI: Glyph-based visualization of tensors, scalar visualization of color by orientation, fractional anisotropy |
| − | * 2D-plot exploring of a single voxel as in [http://www.na-mic.org/Wiki/index.php/Slicer3:FourDAnalysis | + | *** Visualization as vectors (deformation fields, principal diffusion direction) |
| + | *** Visualization as Ellipsoids or multiquadrics (representation of DT-MRI) | ||
| + | **DCE: visualization of the parameter values extracted from model fitting such as tofts model. | ||
| + | * 2D-plot exploring of a single voxel along the 4th axis as in [http://www.na-mic.org/Wiki/index.php/Slicer3:FourDAnalysis FourDAnalysis module] | ||
* Colormap visualization: Mapping from a 3D vector to the RGB components. Examples are | * Colormap visualization: Mapping from a 3D vector to the RGB components. Examples are | ||
** DT-MRI visualization | ** DT-MRI visualization | ||
** Direction of the deformation field at each voxel | ** Direction of the deformation field at each voxel | ||
| + | **combinations of multichannel volumes (microscopy) | ||
Revision as of 12:40, 3 March 2011
Home < Slicer4:VectorImageVisualizationThe main goal of this page is to set the grounds and goals for a common visualization framework for vector images.
Description of vector images
We consider vector-valued images for the purpose of this project any image composed by several scalar images in which the dimensions and spatial transforms are the same.
Examples of these are:
- DCM-MRI / functional MRI, nowadays handled by Slicer using Junichi's | FourDAnalysis module
- Deformation fields which are the result of a registration process.
- DWI-MRI, currently handled by Slicer.
- DTI-Images could be set under this category but their visualization use-cases are, maybe, far too different from the others.
- More complex representations of diffusion MRI (DSI, Q-Ball, Multishell)
| Image type | 4th axis semantics | Number of samples on the 4th axis |
|---|---|---|
| DCM-MRI / fMRI | Time | not fixed |
| Multi-Channel Data | Contrast | not fixed |
| Deformation field | X,Y,Z components of the transform | 3 |
| DWI-MRI | a function with domain angle x b-value | not fixed |
| DTI-MRI | Components of a symmetric positive definite matrix | 9 (or 6 as there are only 6 independent components) |
| More complex representations of diffusion MRI | spherical harmonic coefficients, angular functions, etc | not fixed |
Basic functionalities
- Multi-component scalar-volume visualization: as with the DWI-images where there is a slider enabling the user to choose which component to visualize
- Split and merge into individual volumes. Concept is partially implemented in split and merge in the interactive editor
- Visualization of derived values:
- dMRI: Glyph-based visualization of tensors, scalar visualization of color by orientation, fractional anisotropy
- Visualization as vectors (deformation fields, principal diffusion direction)
- Visualization as Ellipsoids or multiquadrics (representation of DT-MRI)
- DCE: visualization of the parameter values extracted from model fitting such as tofts model.
- dMRI: Glyph-based visualization of tensors, scalar visualization of color by orientation, fractional anisotropy
- 2D-plot exploring of a single voxel along the 4th axis as in FourDAnalysis module
- Colormap visualization: Mapping from a 3D vector to the RGB components. Examples are
- DT-MRI visualization
- Direction of the deformation field at each voxel
- combinations of multichannel volumes (microscopy)
