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This quickstart walks you through a complete DCEMapper session from launch to output. You will open a NIfTI file, explore the volume slice by slice and across time, optionally preprocess the data to reduce noise, draw a region of interest, and finally run the semi-quantitative pipeline to produce three ready-to-use parametric maps.
1

Launch DCEMapper

Windows executable — double-click DCEMapper.exe.From source — run the following command from the repository root:
python -m src.ui.interface.PyQT_interface
The application window opens with a blank workspace and the menu bar in a deactivated state, waiting for data.
2

Open a NIfTI file

In the menu bar, go to File → Open → Open NIfTI File and select your .nii or .nii.gz volume.Once loaded, the interface activates and arranges itself into three panels:
PanelLocationContents
Slice selectorLeftThumbnail grid of all Z slices; Time Point (T) and FPS sliders
Main canvasCentreFull-resolution view of the selected slice at the current time point
Intensity graphRightPer-voxel signal-intensity curve over time; click log
After loading a BIDS-compliant dataset via File → Open → Open BIDS, DCEMapper automatically detects all subjects and provides Next / Previous subject navigation so you can move through the cohort without re-opening the file dialog each time.
3

Explore the data

Use the following controls to navigate the loaded volume:
ActionControl
Previous / next Z slice← → arrow keys, or click a thumbnail in the left panel
Step backward / forward in time↑ ↓ arrow keys, or drag the Time Point (T) slider
Toggle movie-mode playbackSpace — plays through all time frames at the FPS set by the slider
Show voxel intensity curveClick any point on the main canvas; the right panel updates with that voxel’s signal-over-time curve and logs the click with its 3D coordinates
Pan and zoom the main canvas with the toolbar controls (M for pan, Z for zoom, H to reset home view).
4

Preprocess the data

Preprocessing reduces noise and artefacts before quantitative mapping. It is accessed through the Preprocessing menu in the menu bar:
  1. Select a denoising filter from the available options (e.g. Non-Local Means).
  2. Optionally enable Gibbs artifact suppression.
  3. Click Preprocess.
A preprocessed NIfTI file is saved to the derivatives folder and loaded automatically into the canvas. The ROI toolbar becomes available once preprocessing completes.
Preprocessing is optional but recommended for acquisitions with significant thermal noise or Gibbs ringing, as these artefacts can reduce the reliability of voxel-wise parametric estimates.
5

Generate parametric maps

With preprocessed data loaded, run the semi-quantitative pipeline:
  1. Go to Processed → Type → Semi-quantitative.
  2. Click Process.
DCEMapper computes Relative Contrast Enhancement (RCE) across all time points and saves three compressed NIfTI files to the derivatives folder:
FileDescription
rce_process.nii.gzRelative Contrast Enhancement (4-D, one volume per time point)
rce_max_process.nii.gzMaximum RCE per voxel (3-D)
tto_rce_max_process.nii.gzTime point of peak enhancement per voxel (3-D)
The application switches the canvas colormap to jet and loads rce_process.nii.gz automatically. Use the viewer toolbar button to toggle between the three output maps (RCE, MAX RCE, TTP) within the canvas.

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