Difference between revisions of "Projects:ARRA:SlicerWF:UseCaseScenarios"

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** Data loaded into Slicer for interactive editing of label maps as QC
 
** Data loaded into Slicer for interactive editing of label maps as QC
 
** Results loaded back into XNAT
 
** Results loaded back into XNAT
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* see also [[2009_Summer_Project_Week_Slicer3_XNAT_usecases#Use_Case_3:_Quality_Control_Processing_of_Large_Studies| Hans Johnsons scenario]] for similarities.
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=Use-case MS lesion Assessment=
−
 
 
−
=Use-case MS lesion QC=
 
 
# Workflow "blackbox" generates lesion maps along with lesion coordinates files
 
# Workflow "blackbox" generates lesion maps along with lesion coordinates files
 
# Human Interaction module loads image volumes into Slicer with fiduciary markers for lesion assessment
 
# Human Interaction module loads image volumes into Slicer with fiduciary markers for lesion assessment
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# Detailed Scenario is described below
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 +
'''Step 1 ''' Download Images from Xnat
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Convert T1, T2 images into Slicer3 format
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 +
'''Step 2 ''' (preprocessing):
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Register T2 to T1
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'''Step 3''' (preprocessing)
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 +
Skull Stripping of T1 and T2_registered images
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Step 3A . Generation of Brainmask/ICC
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 +
Step 3B. Manual Editing if Brainmask/ICC
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 +
Step 3C. Skull Stripping per se
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'''Step 4 '''(preprocessing) Optional
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Intensity Normalization to the "gold standard" image(s) in case of automated runs
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'''Step 5''' Generate EM Segmentation Scene from the template.
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'''Step 6''' Load The scene into Slicer3
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 +
'''Step 7''' Adjust input parameters if needed.
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Train or re-train data for intensity distribution
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'''Step 8''' Run EM Segmenter
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'''Step 9''' Repeat Steps 7 and 8 if needed
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'''Step 10''' Save EM Segmented Label Map Volume with Feducials' coordinates
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'''Step 11''' Visual Lesion Assessment
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'''Step 12''' Upload Results to XNat
  
 
=Use-case COPD=
 
=Use-case COPD=
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[[File:WF_IntegrationDiagram_General.jpg]]
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=External use-cases=
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* see also [[2009_Summer_Project_Week_Slicer3_XNAT_usecases#Use_Case_3:_Quality_Control_Processing_of_Large_Studies| Hans Johnsons scenario]] for similarities.

Latest revision as of 22:27, 11 December 2009

Home < Projects:ARRA:SlicerWF:UseCaseScenarios
Back to SPINE ARRA page

Overview

  • Oct-20-2009
  • Meeting with Charles and Alex. Discussed following use-case scenario:
    • Data lives in XNAT
    • Black box processing pipeline applied to data
      • Results back to XNAT after QC for completeness
      • MRML file gets autogenerated
    • Data loaded into Slicer for interactive editing of label maps as QC
    • Results loaded back into XNAT

Use-case MS lesion Assessment

  1. Workflow "blackbox" generates lesion maps along with lesion coordinates files
  2. Human Interaction module loads image volumes into Slicer with fiduciary markers for lesion assessment
  3. Detailed Scenario is described below

Step 1 Download Images from Xnat Convert T1, T2 images into Slicer3 format

Step 2 (preprocessing): Register T2 to T1

Step 3 (preprocessing)

Skull Stripping of T1 and T2_registered images

Step 3A . Generation of Brainmask/ICC

Step 3B. Manual Editing if Brainmask/ICC

Step 3C. Skull Stripping per se

Step 4 (preprocessing) Optional Intensity Normalization to the "gold standard" image(s) in case of automated runs

Step 5 Generate EM Segmentation Scene from the template.

Step 6 Load The scene into Slicer3

Step 7 Adjust input parameters if needed. Train or re-train data for intensity distribution

Step 8 Run EM Segmenter

Step 9 Repeat Steps 7 and 8 if needed

Step 10 Save EM Segmented Label Map Volume with Feducials' coordinates

Step 11 Visual Lesion Assessment

Step 12 Upload Results to XNat

Use-case COPD

WF IntegrationDiagram General.jpg

External use-cases

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