Caret7:Development/DataTypes

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(Caret7 DataTypes)
(Caret7 DataTypes)
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* Consider Dense Timeseries for very high temporal density signals (e.g. lowTR BOLD, MEG/EEG) with very large files, otherwise dense timeseries functionality subsumed into metric/scalar
* Consider Dense Timeseries for very high temporal density signals (e.g. lowTR BOLD, MEG/EEG) with very large files, otherwise dense timeseries functionality subsumed into metric/scalar
* Trajectory: #samples for each modeled fiber + distance from starting point
* Trajectory: #samples for each modeled fiber + distance from starting point
 +
* Can be square or rectangular, dimensions can represent different space (e.g. grey ordinates X white ordinates)
 +
 +
== Parcellated Connectivity ==
 +
* Contains a CIFTI-parcellation as the main header component (the graph theoretic "nodes")
 +
* Contains a connectivity value for each parcel to every other parcel (a graph theoretic "edge")
 +
* Can also contain other nodewise, edgewise, or networkwise graph theoretic data
 +
* At least 8 connectivity entries
 +
* Point and click interaction on surface, volume, volume-surface-outline
 +
* Ability to freeze point and click and explore the values in the node
 +
* Ability to export connectivity map to Scalar/Metric
 +
* Ability to average connectivity across subjects or a arbitrary ROI
 +
* Can be square or rectangular, dimensions can represent different space (e.g. "A" list of parcels X "B" list of parcels)
 +
 +
== Parcellated Timeseries ==
 +
* Parcels by time (lets hold off on this till we are sure it is needed and cannot be incorporated into another format)
== Vector ==
== Vector ==

Revision as of 19:26, 2 August 2011

Contents

Caret7 DataTypes

Scalar/Metric

  • Voxel and vertexwise continuous scalar values.
  • Can be surface (GIFTI), volume (NIFTI), or combined (CIFTI-Dense Timeseries format).
  • Represented internally as CIFTI with original header stored in an array for saving as original file type.
  • For volumes, use implicit or explicit masking (i.e. only store data not equal to zero, or user provides a binary mask file).
  • Ability to save as CIFTI dense timeseries or export to NIFTI volume or GIFTI scalar.
  • Do not composite columns unless requested to do so by user.
  • The user will choose Scalar/Metrics on a per window basis (allow at least 10)
  • Display settings on a per column basis
  • Ability to animate through columns/step through them one at a time (i.e. current dense timeseries functionality)
  • Ability to click on a voxel or vertex and display timeseries graph
  • Ability to display average and eigen timeseries graph for arbitrary ROI
  • Ability to export timecourse for point or arbitrary ROI

Label/Parcellation

  • Voxel and vertexwise labeled integer values
  • Each integer is associated with:
    • Name
    • Color
    • Metadata?
  • Can be surface (GIFTI), volume (NIFTI), or combined (CIFTI-Parcellation*).
  • Represented internally as CIFTI with original header stored in an array for saving as original file type.
  • For volumes, use implicit or explicit masking (i.e. only store data not equal to zero, or user provides a binary mask file).
  • Ability to save as CIFTI parcellation* or export to NIFTI volume or GIFTI label.
  • The user will choose Scalar/Metrics on a per window basis (allow at least 10)
  • Ability to turn on and off different parcels, edit their names, colors, metadata
  • Ability to override medial wall
  • Ability to create labels/parcels in surfaces and volumes using ROI tools
  • Ability to convert single label/parcel to binary (1 is in, 0 is out) scalar file

*A CIFTI-parcellation is simply the header of a parcellated timeseries or connectome file. It stores the vertices and voxels that define each parcel, their names, their colors, and any relevant metadata.

Dense Connectivity

  • Voxel and vertexwise connectivity values
  • Too big to load into RAM (load on demand)
  • At least 8 connectivity entries
  • Point and click interaction on surface, volume, volume-surface-outline
  • Ability to freeze point and click and explore the values in the node
  • Ability to export connectivity map to Scalar/Metric
  • Ability to average connectivity across subjects or a arbitrary ROI
  • Consider Dense Timeseries for very high temporal density signals (e.g. lowTR BOLD, MEG/EEG) with very large files, otherwise dense timeseries functionality subsumed into metric/scalar
  • Trajectory: #samples for each modeled fiber + distance from starting point
  • Can be square or rectangular, dimensions can represent different space (e.g. grey ordinates X white ordinates)

Parcellated Connectivity

  • Contains a CIFTI-parcellation as the main header component (the graph theoretic "nodes")
  • Contains a connectivity value for each parcel to every other parcel (a graph theoretic "edge")
  • Can also contain other nodewise, edgewise, or networkwise graph theoretic data
  • At least 8 connectivity entries
  • Point and click interaction on surface, volume, volume-surface-outline
  • Ability to freeze point and click and explore the values in the node
  • Ability to export connectivity map to Scalar/Metric
  • Ability to average connectivity across subjects or a arbitrary ROI
  • Can be square or rectangular, dimensions can represent different space (e.g. "A" list of parcels X "B" list of parcels)

Parcellated Timeseries

  • Parcels by time (lets hold off on this till we are sure it is needed and cannot be incorporated into another format)

Vector

  • Represent directional information
  • Directed or undirected
  • Voxel and vertexwise vectors
  • Uses:
    • Surface Normals (1 per vertex)
    • Modeled Fiber orientations 3+ per diffusion space voxel (not necessarily the same as anatomy volume)
      • Display on volume slices (2D viewer) as needles
      • Display on surface slices (3D viewer) as needles
      • Color by orientation
      • Color by number
      • fODFs?
    • Gradient Vector (vertices and voxels) for design purposes, currently not used
    • Registration Vector (vertices and voxels) for design purposes, currently not used (represent connectivity-based registration deformation fields?)

Border/Contour

  • Represent deterministic/user drawn borders
  • Drawable by user
  • Creatable from labels or thresholded metrics
  • Ability to assign label/metric inside
  • Has:
    • Name
    • Color
    • Metadata?

Foci

  • Represent vertices or 3D volume points of interest
  • Associated with surface vertex, 3D coordinate, 2D geodesic coordinates or all
  • Has:
    • Name
    • Color
    • Metadata?
  • Ability to assign focus by point and click
  • Ability to assign focus by node number
  • Ability to assign focus by 3D coordinate

Surface

  • Display/analyze surface data
  • Hemispheres: Left, right, or midline
  • GIFTI surface format
  • Types: White, midthickness, pial, other, inflated, very inflated, sphere, flat
  • Topology: Closed, Open(cut? what is the difference)

Anatomy Volume

  • Display/analyze volume data
  • NIFTI format
  • Can provide binary additional NIFTI volume as a mask (i.e. display only voxels within mask)

Transformations

  • Affine matrix (world format or FLIRT format?)
  • Generic FSL nonlinear warpfield NIFTI volume (eventually...)
  • Deformation map
  • Deformed spherical surface
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