I N F O R M A T I O N

Analysis Guide

Step-by-step instructions for every analysis type available in QAF — from spectral linearity to material quantification.

Software Analyses.

Core image quality assessment modules

01 Spectral Linearity −
Terminology

Spectral Linearity measures how linearly a material's response changes across different energy bins or concentrations. It evaluates the consistency of material properties (HU or linear attenuation coefficients) across energy levels in spectral CT imaging.

How to Perform
  1. Select Analysis Type: Navigate to Software → Spectral Linearity. Choose HU or Linear Attenuation (cm⁻¹) scale.
  2. Upload Images: Upload DICOM images containing your material samples.
  3. Material Setup: Select the material (e.g., Iodine, Gadolinium) and set up concentrations.
  4. ROI Selection: For HU: measure air/water references first. Draw ROIs on material samples at different concentrations.
  5. Analysis Scope: Choose Across Concentration or Across Energy Bin.
  6. Generate Plot: Create linearity plots to visualize the relationship.
Tip: Ensure consistent ROI placement and sufficient sample sizes for accurate linearity assessment.
02 Signal-to-Noise Ratio (SNR) +
Terminology

SNR quantifies the ratio of signal strength to noise level in an image. Higher SNR indicates better image quality with less noise relative to signal.

How to Perform
  1. Select Analysis: Navigate to Software → Signal-to-Noise Ratio.
  2. Upload Images: Upload DICOM images with the regions you want to analyze.
  3. SNR Setup: Select energy bin and analysis mode (single image or all-images averaged).
  4. ROI Selection: Draw ROIs on homogeneous regions (signal) and background areas (noise). Ensure ROIs > 100 pixels.
  5. Calculate: The system automatically calculates SNR for each ROI.
Tip: Use homogeneous regions for signal measurement. Avoid edges or artifacts that could affect noise calculations.
03 Noise Power Spectrum (NPS) +
Terminology

NPS characterizes the spatial frequency content of noise, describing how noise power is distributed across spatial frequencies using FFT of noise data from uniform ROIs.

How to Perform
  1. Select Type: Choose 1D Radial, 2D Planar, or 3D volumetric NPS.
  2. Upload Images: Upload DICOM images with uniform phantom regions (water phantoms).
  3. Set Voxel Size: Enter physical voxel size in mm — critical for accurate frequency scaling.
  4. Add ROIs: Draw rectangular ROIs on uniform regions (at least 64×64 pixels). Multiple ROIs improve statistics.
  5. Calculate: Run NPS for all ROIs and images.
  6. View Results: 1D plots, 2D heatmaps, or 3D surface plots per energy bin.
Tip: Use uniform water phantoms. Avoid artifacts and non-uniformities. Correct voxel size is essential for frequency accuracy.
04 Modulation Transfer Function (MTF) +
Terminology

MTF measures spatial resolution by quantifying contrast preservation at different spatial frequencies. Derived from PSF (point/wire sources) or LSF (edge spread function differentiated, then FFT).

How to Perform
  1. Upload Images: Upload DICOM images with high-contrast edges, thin wires, or point structures.
  2. Set Voxel Size: Enter physical voxel size for spatial frequency calculations.
  3. Signal ROI: Draw a circle (wire/point) or rectangle/line (edges) on the high-contrast feature.
  4. Background ROI (optional): Draw on a uniform background for subtraction.
  5. Calculate: System calculates FWHM, MTF at 10% and 50% thresholds per energy bin.
Tip: Circle ROI is best for wire/point sources; rectangle or line for edges. Ensure the feature is well-centered.

MIQ Analyses.

Material Identification & Quantification (Advanced tier)

05 Material Decomposition +

Material Decomposition separates multi-energy CT images into material-specific basis images (water, iodine, calcium) using calibration data from known samples.

  1. Navigate to MIQ → Material Quantification
  2. Upload multi-energy DICOM images
  3. Add materials with densities and concentrations
  4. Measure calibration ROIs for each material/concentration
  5. Choose NNLS (recommended) or Direct decomposition
  6. View material-specific density maps
Note: Requires Advanced tier subscription. All materials must have ROI measurements before decomposition.
06 Material Identification +

Material Identification identifies unknown materials by comparing density map predictions with ground truth energy images. Calculates accuracy, precision, recall, and F1-score.

  1. Complete Material Decomposition first
  2. Navigate to MIQ → Material Identification
  3. Select energy bin and target material
  4. Draw target and background ROIs
  5. Set density threshold and perform identification
Note: Requires completed Material Decomposition results and Advanced tier.
07 Material Quantification +

Material Quantification determines concentration of specific materials using calibration data from known samples. Builds a calibration matrix from ROI measurements.

  1. Navigate to MIQ → Material Quantification
  2. Upload DICOM images and define materials
  3. Measure calibration ROIs for each material/concentration
  4. System builds calibration matrix automatically
  5. Draw ROIs on unknown regions to quantify
Note: Accurate quantification depends on proper calibration with known material samples.

Tools Analyses.

Image processing utilities

08 ROI Analysis +

ROI Analysis calculates statistical metrics (mean, std, min, max) for user-selected regions across multiple energy bins.

  1. Navigate to Tools → ROI Analysis
  2. Upload DICOM images and select slice/energy bin
  3. Toggle HU conversion if desired
  4. Draw circular or rectangular ROI on the image
  5. Click Calculate to get statistics for all energy bins
Tip: Larger ROIs provide better statistical significance. HU conversion requires air/water calibration.
09 Histogram Analysis +

Histogram Analysis generates frequency distributions of pixel values in selected ROIs — single image or averaged across all slices.

  1. Navigate to Tools → Histogram Analysis
  2. Upload DICOM images and draw ROIs
  3. Set scope (selected image or all images) and bin count
  4. Generate histogram and review interactive plot
  5. Export to Excel or CSV
Tip: Multiple ROIs provide better statistical representation. "All Images" scope averages across slices.
10 Line Profile Analysis +

Line Profile extracts intensity values along drawn lines, creating 1D profiles for analyzing edges, boundaries, and spatial gradients.

  1. Navigate to Tools → Line Profile Analysis
  2. Upload DICOM images and select slice/energy bin
  3. Draw lines on the image (multiple lines to compare)
  4. Adjust line width for smoother profiles
  5. View interactive intensity vs. distance plot
Tip: Wider line widths provide smoother profiles by averaging across perpendicular pixels.
11 HU Conversion +

HU Conversion converts raw attenuation values to the standardized Hounsfield Unit scale (water = 0 HU, air = −1000 HU) using air/water calibration.

  1. Navigate to Tools → HU Conversion
  2. Upload DICOM images
  3. Draw ROIs on air and water regions, measure mean values
  4. System calculates conversion parameters automatically
  5. Toggle "Use HU" to view images in HU scale
  6. Download converted DICOM or PNG files
Note: HU values are energy-dependent in spectral CT. Calibrate per energy bin for best accuracy.

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