Difference between revisions of "2009 Summer Project Week 4D Imaging"
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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 at Project Week 2009]] | ||
Revision as of 21:04, 22 June 2009
Home < 2009 Summer Project Week 4D Imaging
Screen shot of 4D Analysis Module
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:
- 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
4D Meeting at Project Week 2009
References
The preliminary module implementation is described in Slicer3:FourDAnalysis.
