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 part of the ability to handle such multi-dimensional volume in the DWI infrastructure:

• Dicom to nrrd, the slider in the volumes module to look at any of the individual volumes in DWI.
• Junichi's 4D mrml node takes a different approach but ultimately also allows to look at a time point at a time through a slider.
• Brainsfit has the ability to register such multi data sets to each other and Gtract has a first solution which is engineered for DWI
• 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.

Multi volumes can be processed in specialized ways. Existing examples are:

• Parametric analysis:
  • DTI estimation from DWI
  • Tofts parameter estimation from DCE
• Segmentation:
  • EM segmentation from multi-channel morphology data

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

Processing

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