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ThomasMr99 edited this page Jan 29, 2025 · 20 revisions

These tutorials present various use cases for working with Voreen. The examples demonstrate how to utilize the software effectively.

Preprocessing Flow Data

Description:
The following workflow loads a NIfTI file, processes certain properties, and outputs the data in various selectable formats.

Processors:
VolumeListSource, FlowMapCreator, VolumeListSpacing, VolumeListOffset, VolumeListRealWorldMapping, VolumeListSave

Arrangement:

preprocessing_flow_data

Operations:

  • VolumeListSource: Loads volume data, for instance, in the NIfTI format.
  • FlowMapCreator: Creates a vector field based on the data. The processor’s properties allow manipulation of the
  • vector field’s orientation and channels.
  • VolumeListSpacing** & VolumeListOffset: Provides options to adjust the volume data spacing (in mm) and the offset.
  • VolumeListRealWorldMapping: Enables various mappings, such as scale and offset adjustments.
  • VolumeListSave: Saves the processed volume data in one of the available data formats.

Random Walker Segmentation

The Random Walker Segmentation algorithm is a graph-based method for image segmentation. It assigns labels to pixels(or voxels in 3D) based on probabilities derived from random walks starting at seed points. These seed points are defined by the user as belonging to specific regions, such as "foreground" or "background." The algorithm then calculates the likelihood of each unassigned pixel being reached by a random walker starting from each seed. This approach is particularly effective for handling noisy data and achieving smooth segmentations while respecting the boundaries in the input image.

This use case demonstrates the application of the random walker algorithm on the walnut.vvd dataset using a predefinedsample workspace. The focus is on Voreen's Application Mode rather than pipeline construction.

To access the segmentation-randomwalker.vws workspace in Voreen, follow these steps:
File → Open Workspaces → Workspaces → segmentation-randomwalker.vws → Open

A canvas element and a large network will now appear. Since the network does not require manipulation in this case, switch the view from Network Mode to Application Mode for easier handling. This can be done via the toolbar Toolbar.

After these steps, your screen should resemble the following:

segmenatiton_random_walker_in_application_mode

As shown, this workspace takes 3D data and displays it in a 2x2 grid, featuring a 3D view alongside three slices representing different planes: $XY, \ XZ, \ YZ$ (or, in medical terms, the axial, sagittal, and coronal planes).

Additionally, predefined properties (Input; 2D Rendering, RandomWalker, Seeds, and Output) enable users to interact with the visualization.

Operations in the Properties Space:

  • Input:
    Use Clear Volume to remove the current input file and Load Volume to load new data.
  • 2D Rendering:
    Adjust the transfer function for visualization or explore different data slices.
  • Random Walker:
    Select from various noise models in the Noise Model dropdown for the segmentation.
  • Seeds:
    Clear all existing seeds for segmentation.
  • Output:
    Save either the probabilities file or the segmentation file as output.

Operations in the Canvas Space:

  • Adjust the slice number for each plane using the scroll wheel.
  • Add or delete seeds in each plane with the following operations:
    • Add a foreground seed: Ctrl + Left Click
    • Delete a foreground seed: Ctrl + Right Click
    • Add a background seed: Shift + Left Click
    • Delete a background seed: Shift + Right Click

##Further tutorials:

Vortex Coreline Extraction
Vessel Graph Extraction
OpenLB

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