TubeTK/Documentation/InteractivePDFSegmenter

Documentation

Parameters

• Input Volume 1: The image to be segmented
• Input Volumes 2 and 3 (optional): TODO
• Output Volume: The segmentation results
• Label Map: A rough initial segmentation provided as input to the algorithm
• Void Id: Value that specifies nothing in the label map
• Erosion Radius: TODO
• Hole Fill Iterations: TODO
• False Positive Ratio: TODO
• Probability Smoothing Standard Deviations: TODO
• Draft Mode: TODO
• Reclassify Object Mask: Whether or not to TODO
• Reclassify Not Object Mask: Whether or not to TODO

Tutorial

Tutorial Data

• The 2D brain image used in this example is distributed as part of Slicer4, and is located in Slicer4/Testing/Data/Input/brainSliceDOUBLE.mha
• In this example, we will attempt to segment gray matter, white matter and cerebrospinal fluid (CSF)

Tutorial Steps

1. Load brainSliceDOUBLE.mha:
   • File -> Add Volume
2. Open the Interactive PDF Segmenter module
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3. Set the input and output volumes
   • Input Volume 1: brainSliceDOUBLE
   • Input Volume 2 (optional): None
   • Input Volume 3 (optional): None
   • Output Volume: Create new volume
     • Creates a new volume called "Volume": this will hold the final segmentation
4. Set the view layout to "Red slice only"
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5. Create the label map roughly outlining the structures to be segmented and the background
   • Label Map: Create new volume
     • Creates a new volume called "Volume1": this will hold the input label map
   • A small version of Slicer's Editor module is embedded into the Interactive PDF Segmenter
   • Create a label map roughly outlining the structures of interest and the background by using the paint, erase and threshold functions
     • Click on the "Paint" button to begin editing
     • Use a different label color for each structure of interest: choose the label by clicking the colored push button
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     • Create a label for the background as well
   • In the following example, green represents gray matter, yellow represents white matter, and brown represents the cerebrospinal fluid (CSF):
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   • Void Id: 0
6. Specify the segmentation parameters
   • The goal segmentation buttons provide example parameters depending on whether the shapes of the expected segmentations are jagged, smooth or intermediate
   • In this example, we will use custom parameters
   • Erosion Radius: 0
   • Hole Fill Iterations: 2
   • False Positive Ratio: 1.00
   • Probability Smoothing Standard Deviation: 1.00
   • Draft Mode: Off
   • Reclassify Object Mask: On
   • Reclassify Not Object Mask: On
7. Run the segmentation
   • Click the "Segment" button
   • Select "Volume" as the label map to view the results
   • Pixels that do not have a label value remain un-classified
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   • To view the label outlines, select "Show label volume outlines"
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