Difference between revisions of "2009 Summer Project Week 4D Imaging"

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[[2009_Summer_Project_Week_4D_Imaging_discussion| 4D Meeting at Project Week 2009]]
 
  
 
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*Initial implementation of 4D Image module. The module is available at http://svn.slicer.org/Slicer3/trunk/Modules/FourDImage
 
*Initial implementation of 4D Image module. The module is available at http://svn.slicer.org/Slicer3/trunk/Modules/FourDImage
 
*Initial implementation of 4D Analysis module. The Python interface has to be fixed. The module is available at http://svn.slicer.org/Slicer3/trunk/Modules/FourDAnalysis
 
*Initial implementation of 4D Analysis module. The Python interface has to be fixed. The module is available at http://svn.slicer.org/Slicer3/trunk/Modules/FourDAnalysis
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*[[2009_Summer_Project_Week_4D_Imaging_discussion| 4D Meeting]] was organized.
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**Demo of 4D module
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**4D Bundle
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**Application
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**Memory usage
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**Pipeline processing
  
  

Latest revision as of 14:40, 26 June 2009

Home < 2009 Summer Project Week 4D Imaging

Key Investigators

  • BWH: Junichi Tokuda, Wendy Plesniak, Nobuhiko Hata
  • WFU:Craig A. Hamilton

Objective

Implement a set of 3D Slicer modules to handle 4D images in 3D Slicer for perfusion analysis, cardiac, etc. including:

  • Handling
    • Loading 4D volume
    • Scroll time-line
    • 4D image editing
    • Recording 4D Gated US
  • Processing
    • Image registration for motion compensation
  • Analysis
    • Perfusion analysis: fitting pharmacokinetic model
  • We are going to organize 4D imaging session during the meeting.

Please join us, if you are interested in.


Approach, Plan

We will work on the following tasks:

  • Implementation of 4D Image module that provides:
    • 4D image loading: Loading a series of 3D images from a specified director. The data can be either in DICOM or NRRD format.
    • Time line scroll-bar interface: scrolling the frame in time-direction. It allows you to scroll the frame for foreground and background screens independently to compare two images at the different time points.
    • Frame editing: Reorganizing the time series data (optional)
  • Implementation of 4D Analysis module that provides:
    • Intensity plot: Plotting temporal changes of intensities at specified regions. This feature is useful for analyzing dynamic contrast images.
    • Model fitting: A python interface to analyze intensity curves obtained from the 4D images. The interface is useful to fit pharmacokinetic models to intensity curves to obtain perfusion parameters.
  • Investigating BatchMake as an infrastructure for time-series image processing.
    • 4D Cropping: Cropping volumes in a time-series data using BatchMake.
    • 4D Image registration: Registering each volume frame to a key-frame to compensate organ motion.
    • Image registration using cluster (Optional)

Progress

Before the project week, we have completed:


References

The preliminary module implementation is described in Slicer3:FourDAnalysis.

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