TubeTK/Documentation/InteractivePDFSegmenter

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Revision as of 16:39, 7 January 2011 by 97.65.130.163 (talk)
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Documentation

Overview

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
    • InteractivePDFSegmenterTutorial step2.png
  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"
    • InteractivePDFSegmenterTutorial step4a.png
    • InteractivePDFSegmenterTutorial step4b.png
  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
    • InteractivePDFSegmenterTutorial step5a.png
      • 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):
    • InteractivePDFSegmenterTutorial step5b.png
    • 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
    • InteractivePDFSegmenterTutorial step7a.png
    • InteractivePDFSegmenterTutorial step7b.png
    • To view the label outlines, select "Show label volume outlines"
    • InteractivePDFSegmenterTutorial step7c.png
    • InteractivePDFSegmenterTutorial step7d.png