Cluster Mass

Compute raw statistic mass, threshold-excess mass and peak for face-connected suprathreshold clusters; conventions are explicit and no null distribution is invented.

Description

Cluster mass accumulates statistic values over connected suprathreshold voxels.

Cluster mass accumulates statistic values over connected suprathreshold voxels. Excess mass subtracts the threshold once per voxel and answers a different question.

The tool returns clusterMasses (cluster masses); clusterExcessMasses (cluster excess masses); clusterPeakStatistics (cluster peak statistics). Input measurements and model parameters are supplied by the caller; the tool computes the stated summary rather than acquiring those measurements.

When to use Cluster Mass

Use Cluster Mass when you already have voxelStatistics, dimensions, threshold and want clusterMasses, clusterExcessMasses, clusterPeakStatistics. This is useful for checking a supplied calculation, documenting a measurement convention, or comparing observations prepared on the same basis.

How to use Cluster Mass and understand its results

Enter voxelStatistics, dimensions, threshold using the field table below. Match the units, ordering and data boundaries described in the calculation.
Run the tool after checking the stated bounds and matching paired observations or categories. A malformed request gives a tool error rather than a usable measurement.
Read clusterMasses, clusterExcessMasses, clusterPeakStatistics. Use the calculation and interpretation below to distinguish amounts, ratios, signs and decision flags where applicable.
Review the supplied parameters and assumptions before using the result in a report or comparing it with another observation.

Input field	Meaning	Value type and bounds	Requirement
voxelStatistics	Voxel statistics	list of number	Required
dimensions	Dimensions	list of number	Required
threshold	Threshold	number	Required

Select statistics at least the positive threshold and find six-connected face-adjacent components in x-fastest flattening order. Return mass, excess mass and peak for each component.

mass = Σstatistics; excess mass = Σ(statistic−threshold)

The symbols refer to the supplied quantities or generated values described above; unit conversions and comparison boundaries follow the stated implementation.

json

{
  "input": {
    "voxelStatistics": [
      2,
      2,
      0,
      3
    ],
    "dimensions": [
      4,
      1,
      1
    ],
    "threshold": 1
  },
  "output": {
    "clusterMasses": [
      4,
      3
    ],
    "clusterExcessMasses": [
      2,
      2
    ],
    "clusterPeakStatistics": [
      2,
      3
    ]
  }
}

Limitations and assumptions

No corrected cluster significance is calculated. Values exactly at threshold join a cluster but add zero excess mass.

Numerical inputs must be finite. The tool checks its declared input shape and calculation constraints; those checks do not verify the quality, calibration or representativeness of the supplied observations.

Alternative or Complementary methods

Cluster Extent: Find face-connected 3D suprathreshold voxel components using inclusive thresholding, x-fastest flattening and a supplied voxel volume; no inferential cluster p-values are produced. TFCE Value: Approximate nonnegative TFCE by bounded midpoint height integration over face-connected voxel clusters; extent is voxel count, not physical volume, and inference requires an external permutation null.

Methodological background: Threshold-free cluster enhancement.^[1]

References

Threshold-free cluster enhancement — Smith and Nichols; FMRIB technical report

Similar or alternative tools

Cluster Extent
Find face-connected 3D suprathreshold voxel components using inclusive thresholding, x-fastest flattening and a supplied voxel volume; no inferential cluster p-values are produced.
TFCE Value
Approximate nonnegative TFCE by bounded midpoint height integration over face-connected voxel clusters; extent is voxel count, not physical volume, and inference requires an external permutation null.