Neuromelanin Contrast

Compute neuromelanin-sensitive ROI/reference contrast and CNR using reference sample SD; scanner sequence and ROI selection are external, and contrast is not neuron density.

Description

Reference-normalized neuromelanin contrast compares regional and reference mean signals.

Reference-normalized neuromelanin contrast compares regional and reference mean signals. Dividing their difference by reference variability gives a distinct contrast-to-noise measure.

The tool returns roiMean (roi mean); referenceMean (reference mean); contrastPercent (contrast percent); contrastToNoiseRatio (contrast to noise ratio). Input measurements and model parameters are supplied by the caller; the tool computes the stated summary rather than acquiring those measurements.

When to use Neuromelanin Contrast

Use Neuromelanin Contrast when you already have roiSignals, referenceSignals and want roiMean, referenceMean, contrastPercent, contrastToNoiseRatio. This is useful for checking a supplied calculation, documenting a measurement convention, or comparing observations prepared on the same basis.

How to use Neuromelanin Contrast and understand its results

Enter roiSignals, referenceSignals 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 roiMean, referenceMean, contrastPercent, contrastToNoiseRatio. 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
roiSignals	Roi signals	list of number	Required
referenceSignals	Reference signals	list of number	Required

Use positive nonempty signals and at least two varying reference observations. ROI and reference list lengths need not match.

contrast% = 100(ROImean−referenceMean)/referenceMean; CNR = (ROImean−referenceMean)/sampleSD(reference)

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

json

{
  "input": {
    "roiSignals": [
      120,
      140
    ],
    "referenceSignals": [
      90,
      100,
      110
    ]
  },
  "output": {
    "roiMean": 130,
    "referenceMean": 100,
    "contrastPercent": 30,
    "contrastToNoiseRatio": 3
  }
}

Limitations and assumptions

No segmentation, sequence calibration or neuromelanin concentration is estimated. Reference variability includes more than scanner noise.

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

Myelination Index: Compute reference-normalized T1w/T2w ROI ratios as an explicit myelin-sensitive imaging index; intensity bias correction is external and this is not a myelin fraction. Contrast to Noise Ratio: Estimate signed two-ROI CNR using difference-noise SD/√2 from independent matched acquisitions; unlike reference-ROI contrast metrics, the noise estimate is independent.

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

Myelination Index
Compute reference-normalized T1w/T2w ROI ratios as an explicit myelin-sensitive imaging index; intensity bias correction is external and this is not a myelin fraction.
Contrast to Noise Ratio
Estimate signed two-ROI CNR using difference-noise SD/√2 from independent matched acquisitions; unlike reference-ROI contrast metrics, the noise estimate is independent.