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.
Description
Cluster extent counts connected selected voxels and converts that count to physical volume.
Cluster extent counts connected selected voxels and converts that count to physical volume. Connectivity and voxel size determine the interpretation.
The tool returns clusterVoxelCounts (cluster voxel counts); clusterVolumesMm3 (cluster volumes mm3); largestClusterVoxelCount (largest cluster voxel count). 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 Extent
Use Cluster Extent when you already have voxelStatistics, dimensions, threshold, voxelVolumeMm3 and want clusterVoxelCounts, clusterVolumesMm3, largestClusterVoxelCount. This is useful for checking a supplied calculation, documenting a measurement convention, or comparing observations prepared on the same basis.
How to use Cluster Extent and understand its results
- Enter voxelStatistics, dimensions, threshold, voxelVolumeMm3 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 clusterVoxelCounts, clusterVolumesMm3, largestClusterVoxelCount. 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 |
| voxelVolumeMm3 | Voxel volume mm3 | number | Required |
Apply an inclusive positive statistic threshold and six-neighbor face connectivity to a matching three-dimensional grid. Return each count and volume, plus largest count or zero when none qualify.
cluster volume = voxelCount × voxelVolumeMm³ The symbols refer to the supplied quantities or generated values described above; unit conversions and comparison boundaries follow the stated implementation.
{
"input": {
"voxelStatistics": [
2,
2,
0,
3
],
"dimensions": [
4,
1,
1
],
"threshold": 1,
"voxelVolumeMm3": 2
},
"output": {
"clusterVoxelCounts": [
2,
1
],
"clusterVolumesMm3": [
4,
2
],
"largestClusterVoxelCount": 2
}
}Limitations and assumptions
Diagonal contacts do not connect clusters. Extent alone is not a corrected p value or lesion segmentation.
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 Mass: Compute raw statistic mass, threshold-excess mass and peak for face-connected suprathreshold clusters; conventions are explicit and no null distribution is invented. Euler Characteristic: Count the unique cells of the union of closed voxel cubes and compute V−E+F−C; edge/corner contacts share cells, unlike a six-connected component convention.
Methodological background: Threshold-free cluster enhancement.1
References
-
Threshold-free cluster enhancement — Smith and Nichols; FMRIB technical report
Similar or alternative tools
- 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.
- Euler Characteristic
Count the unique cells of the union of closed voxel cubes and compute V−E+F−C; edge/corner contacts share cells, unlike a six-connected component convention.