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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 4D Image Module and 4D Analysis module.
  • 4D CT/MRI/US
  • 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)
  • RTSTRUCT, radiotherapy planning structures
Image type 4th axis semantics Number of samples on the 4th axis
DCM-MRI / fMRI / 4D CT, MRI US 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
RTSTRUCT structure labeling (one bit per structure) 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
    • 4D Image editing function is also partially implemented in 4D Image Module.
  • 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)
    • Dynamically increase (or decrease) vector size
    • Select a bit within the vector
    • Display outline, shading, other visualization

Use Case Scenario

  • R: RECIST analysis
  • M: Time Series Analysis of MRI's from an MS Patient
  • P: Time Series Analysis of SUV values in MR/CT PET
  • D: Dynamic Contrast Enhancement (DCE)

Common Features and Needs

  • These are all time series of scalar volumes and need to be organized in a number of dimensions: space, time, signal intensities, feature space (such as channels in multichannel data, gradient strength in dMRI data, etc.)
  • Typically the volumes need to be registered to each other in order to organize them in space: Fusion between the channels, fusion across the time points
    • What is the best way to pass 4D image data to command line modules?
  • bias correction is often needed: MR, PET, CT(?)
    • No bias correction for CT
  • Window/Level:
    • Allow manual setting of w/l for the reference time point.
    • CT: one w/l for all time points, PET, MR: the SUV concept could be expanded to MRI: use one or two user selected/drawn ROI to adjust window level across time points.

Viewing and Analysis

  • view across time: movie (loop, bounce)
  • graphing: resample across time
  • need to do analysis across time: ROI's (label map) for voxel statistics across time. Create spreadsheet / graph as result.
  • need to store the organizational frame work. When the patient comes for the next scan we need ability to add a time point, fix data (registration, w/l, update spreadsheet/graph)


Initial Setup of a MultiVolumeContainer

  • Assume that all data have been loaded into Slicer already
  • Create a new MultiVolumeContainer.
    • MVC's are always multi-channel. Single channel is just a special case.
    • User specifies the number of channels.
    • one of the volumes is assigned as the reference volume (default is the first loaded, user can change manually by clicking a checkbox)

Things you can do with MVC's

  • editing the MVC by adding or removing time points or changing their order
  • change the reference volume
  • assign registration types between the channels and between the time points
  • execute the registration cascade
  • adjust W/L across time for each channel using histogram equalization with manual override
  • across time analysis: label map with multiple ROI's will give across time statistics
    • special case for SUV across time
  • RECIST: determination at each time point, use previous one as initialization
  • Formulas: DCE requires Tofts, NukMed uses other, similar formulas, DWI to DTI uses Stejskal.


MultiVolumeContainer MRML Node

  • vtkMRMLDiffusionImageVolumeNode is a good start?
  • Class hierarchy (names are tentative)
    • vtkMRMLScalarVolumeNode
      • vtkMRMLTensorVolumeNode (?)
        • vtkMRMLMultiVolumeNode
          • vtkMRMLTimeSeriesVolumeNode
          • vtkMRMLMultiChannelVolumeNode
          • vtkMRMLVectorFiledVolumeNode
          • vtkMRMLDiffusionWeightedImageVolumeNode
          • vtkMRMLDiffusionTensorImageVolumeNode
          • <More complex representations of diffusion MRI>
          • vtkMRMLStructureLabelingVolumeNode

4D Image Editor Module

  • Create / edit multi volume container

Time-series Image Analysis Modules

  • Time-intensity plot + curve analysis

4D Image Control Widget

  • GUI widget that can be embedded in any GUI modules
  • Node selector + slider to switch volume + 4th value display (time, b-value, etc.)