Gibbs Ringing Checker
Screen overshoot/undershoot around a caller-selected intensity edge relative to plateau contrast; this finds ringing-compatible features, not a specific Gibbs-artifact diagnosis.
Description
A sampled edge profile may rise above its high plateau or fall below its low plateau.
A sampled edge profile may rise above its high plateau or fall below its low plateau. Normalizing those excursions by the step height yields comparable ringing fractions.
The tool returns overshootFraction (overshoot fraction); undershootFraction (undershoot fraction); criterionExceeded (criterion exceeded). Input measurements and model parameters are supplied by the caller; the tool computes the stated summary rather than acquiring those measurements.
When to use Gibbs Ringing Checker
Use Gibbs Ringing Checker when you already have edgeProfile, lowPlateau, highPlateau, overshootCriterionFraction and want overshootFraction, undershootFraction, criterionExceeded. This is useful for checking a supplied calculation, documenting a measurement convention, or comparing observations prepared on the same basis.
How to use Gibbs Ringing Checker and understand its results
- Enter edgeProfile, lowPlateau, highPlateau, overshootCriterionFraction 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 overshootFraction, undershootFraction, criterionExceeded. 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 |
|---|---|---|---|
| edgeProfile | Edge profile | list of number | Required |
| lowPlateau | Low plateau | number | Required |
| highPlateau | High plateau | number | Required |
| overshootCriterionFraction | Overshoot criterion fraction | number | Required |
Require a nonempty profile, high>low and a nonnegative criterion. Flag an excursion strictly above the criterion; equality is not flagged.
overshoot = max(0,maxProfile−high)/(high−low); undershoot = max(0,low−minProfile)/(high−low) The symbols refer to the supplied quantities or generated values described above; unit conversions and comparison boundaries follow the stated implementation.
{
"input": {
"edgeProfile": [
0,
0,
1.1,
1,
1
],
"lowPlateau": 0,
"highPlateau": 1,
"overshootCriterionFraction": 0.05
},
"output": {
"overshootFraction": 0.10000000000000009,
"undershootFraction": 0,
"criterionExceeded": true
}
}Limitations and assumptions
The tool measures supplied samples without fitting plateaus, estimating a Gibbs model or removing ringing.
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
Spatial Smoothing FWHM: Build a normalized truncated 1D Gaussian kernel from physical FWHM and voxel spacing; distinct from estimating residual smoothness from derivative covariance. MRI Signal to Noise Ratio: Estimate single-channel magnitude MRI SNR using Rayleigh background SD correction; parallel imaging, multicoil noise and spatially varying g factors violate this model.
Methodological background: Measures of scale: sample variance and standard deviation.1
References
-
Measures of scale: sample variance and standard deviation — NIST/SEMATECH
Similar or alternative tools
- Spatial Smoothing FWHM
Build a normalized truncated 1D Gaussian kernel from physical FWHM and voxel spacing; distinct from estimating residual smoothness from derivative covariance.
- MRI Signal to Noise Ratio
Estimate single-channel magnitude MRI SNR using Rayleigh background SD correction; parallel imaging, multicoil noise and spatially varying g factors violate this model.