Afni3dclust

To see the AFNI postscript documentation please go here.

To read the help documentation generated from the command line go here.

To learn about afni data types follow this link.

Invocation

java Afni3dclust

For information on how to invoke the command line program, 3dclust, please go here.

Afni3dclust window

• Input dataset
  The dataset to be used as input. Afni3dclust takes one 3d datasets as input. However, a 3d + time dataset can be used if the sub-bricks for intensity and threshold data are given in the Editing Options.
• Output prefix
  An output dataset will be generated with this prefix.
• Cluster Connection Radius
  The cluster connectivity distance in mm. It is required that this value be positive and should be slightly over one voxel width.
• Minimum Cluster Volume
  It is required that this value not be zero and in micro liters.
• Editing Options...
• No volume editing
  Do not do any volume editing to the dataset.
• Use nearest neighbor clustering
  Let 3dclust search the top, bottom, left, right, forward, and backward voxels for clusters.
• Cluster for each distinct value
  Create clusters for each distinct value regardless of connection radius and minimum cluster value.
• Cluster voxels with same values
  Cluster voxels together only if they have exactly the same value.
• Stretch to MNI brain
  If the input dataset is in tlrc coordinates, 3dclust will try to map xyz-coordinates to the MNI template brain.
• Assume 1 mm voxel dimensions
  Read the dataset as having voxels that are 1 mm on each side. This option can simplify calculations for the connection radius and cluster volume.
• Use signed voxel intensities
  Use the signed voxel intensities (not the absolute values) for calculation of mean and standard error of mean (SEM).
• Summarize only
  Write out only the total nonzero voxel count and volume for each dataset.
• Verbose
  Write out extra information about cluster calculations.

• Menubar
• Toolbar
• Output window