Difference between revisions of "2011 Winter Project Week:Breakout Multi-Image Engineering"

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=Current State=
 
=Current State=
We have part of the ability to handle such multi-dimensional volume in the DWI infrastructure:  
+
We have parts of the ability to handle such multi-dimensional volume in the DWI and 4D infrastructures:  
*Dicom to nrrd, the slider in the volumes module to look at any of the individual volumes in DWI.
+
 
*Junichi's TimeSeriesBundleNode is a mrml node to organize 4D data.
+
==I/O==
*Brainsfit has the ability to register such multi data sets to each other and Gtract has a first solution which is engineered for DWI
+
*Dicom to nrrd
*Compareview would allow to show multi data in compareviewers. When we have a few volumes, then we can display all. If its a large number of volumes, we will only be able to display a few. Some engineering work will be needed to make this easy on the user.
+
*TimeSeriesBundleNode is a mrml node to organize 4D time series data.
 +
 
 +
==Display==
 +
*In the volumes module, a slider allows to look at any of the individual volumes in DWI data set.
 +
*In the 4D display module, a movie player like capability exists
 +
*The dti infrastructure allows the display of derived scalar values such as FA and color by orientation
  
 
==Existing Processing capabilities==
 
==Existing Processing capabilities==
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*Segmentation:
 
*Segmentation:
 
**EM segmentation from multi-channel morphology data
 
**EM segmentation from multi-channel morphology data
 +
*Registration
 +
**Brainsfit has in principle the ability to register multi data sets to each other and Gtract has a first solution which is engineered for DWI
 +
  
 
=The Need=
 
=The Need=
Line 37: Line 45:
 
==Display==
 
==Display==
 
*we should create a single visualization infrastructure to handle multi data: compare viewers, rgb channels, time series movies: equivalent slice viewers and 3D viewers
 
*we should create a single visualization infrastructure to handle multi data: compare viewers, rgb channels, time series movies: equivalent slice viewers and 3D viewers
 +
*Compareview should allow to show multi data in compareviewers. When we have a few volumes, then we can display all. If its a large number of volumes, we will only be able to display a few. Some engineering work will be needed to make this easy on the user.
 
==Processing==
 
==Processing==
 
*common api for processing: EM segmentation, pharmacokinetic models, DWI filtering, tensor estimation should all plug into the data in the same way.
 
*common api for processing: EM segmentation, pharmacokinetic models, DWI filtering, tensor estimation should all plug into the data in the same way.

Revision as of 12:02, 3 January 2011

Home < 2011 Winter Project Week:Breakout Multi-Image Engineering
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Agenda breakout session: Multi-Image Engineering in slicer

Wednesday 8-10am

Session Leaders: Jim Miller, Steve Pieper, Alex Yarmakovich, Junichi Tokuda, Demian Wasserman

Background

Increasingly, we have data in slicer which are multi something. Examples are:

  • multi-channel (T1, T2, flair, dual echo, etc.)
  • DWI
  • rgb and other multi-channel images
  • time series

Current State

We have parts of the ability to handle such multi-dimensional volume in the DWI and 4D infrastructures:

I/O

  • Dicom to nrrd
  • TimeSeriesBundleNode is a mrml node to organize 4D time series data.

Display

  • In the volumes module, a slider allows to look at any of the individual volumes in DWI data set.
  • In the 4D display module, a movie player like capability exists
  • The dti infrastructure allows the display of derived scalar values such as FA and color by orientation

Existing Processing capabilities

Multi volumes are processed in Slicer in specialized ways.

  • Parametric analysis:
    • DTI estimation from DWI
    • Tofts parameter estimation from DCE
  • Segmentation:
    • EM segmentation from multi-channel morphology data
  • Registration
    • Brainsfit has in principle the ability to register multi data sets to each other and Gtract has a first solution which is engineered for DWI


The Need

All of the current examples are special cases. If we can generalize those into a single architecture for multi data, there would be a lot of potential for cross-benefits.

I/O

  • We should have a single module to organize the data. DICOM to nrrd is a good start, but we need to be able to handle separate T1 and T2 acquisitions as well. We also need to be able to handle non-dicom data. Perhaps something like: load all data into slicer and associate them inside slicer in a special module. Write out as a single nrrd file.

Display

  • we should create a single visualization infrastructure to handle multi data: compare viewers, rgb channels, time series movies: equivalent slice viewers and 3D viewers
  • Compareview should allow to show multi data in compareviewers. When we have a few volumes, then we can display all. If its a large number of volumes, we will only be able to display a few. Some engineering work will be needed to make this easy on the user.

Processing

  • common api for processing: EM segmentation, pharmacokinetic models, DWI filtering, tensor estimation should all plug into the data in the same way.