Difference between revisions of "Slicer4:VectorImageVisualization"
From Slicer Wiki
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** 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) |
+ | * For RTSTRUCT | ||
+ | ** Dynamically increase (or decrease) vector size | ||
+ | ** Select a bit within the vector | ||
+ | ** Display outline, shading, other visualization | ||
=Use Case Scenario= | =Use Case Scenario= |
Revision as of 17:48, 28 March 2011
Home < Slicer4:VectorImageVisualizationBack to Slicer4 Projects
Contents
Introduction
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)
- RTSTRUCT, radiotherapy planning structures
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 |
RTSTRUCT | structure labeling | 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)
- For RTSTRUCT
- 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
- bias correction is often needed: MR, PET, 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)
Workflows
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.