Slicer4:VectorImageVisualization

The 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.
• 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)