Difference between revisions of "Project Week 25/Multimodal:"

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==Key Investigators==
 
==Key Investigators==
 
<!-- Key Investigator bullet points -->
 
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*Investigator 1 (Affiliation)
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*Guido Gerig (NYU Tandon School of Engineering)
*Investigator 2 (Affiliation)
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*Sungmin Hong (NYU Tandon School of Engineering)
*Investigator 3 (Affiliation)
 
  
  
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! style="text-align: left; width:27%" |  Progress and Next Steps
 
! style="text-align: left; width:27%" |  Progress and Next Steps
 
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|- style="vertical-align:top;"
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<!-- Objective bullet points -->
  
|<!-- Approach and Plan bullet points -->
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3D/4D Ophthalmology Image Anaylsis Framework
  
|<!-- Progress and Next steps (fill out at the end of project week), bullet points -->
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* Read 4D hyperspectral data
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* Viewer and interactor for 3D hi-res image data and 4D hyperspectral data
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* Co-registration between 3D hi-res data and 4D hyperspectral data
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* Cell segmentation in 3D hi-res data
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* Statistics of cells (possibly location, size, distribution)
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* Plot of spectra of selected cells or a region-of-interest
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|}
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<!-- Approach and Plan bullet points -->
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* Review existing modules in 3D Slicer
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** Review existing modules for 4D data viewer, such as, multi-volume viewer extension
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** Try existing segmentation modules in Slicer to see if they can work on SIM data
 +
** Review existing modules for cell statistics after segmentation
 +
 
 +
* Implementation/Integration
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** Implement/integrate 4D hyperspectral data viewer to show image and spectral information.
 +
** Integrate registration functionality for co-registration between 3D hi-res data and 4D hyperspectral data at image level
 +
** Integrate user-initialized level set segmentation for cell segmentation or EM segmentation module
 +
** Implement a viewer and an interactor for cell statistics
 +
 
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* User Manual
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** Create an user manual to comprehend a overview of an extension
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** Guide users to different extensions in a algorithmic flow chart if there are any desired functions (registration, segmentation, or etc.) which are already implemented in existing modules.
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|
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<!-- Progress and Next steps bullet points (fill out at the end of project week -->
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* Hyperspectral Analysis
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** Implemented a module to convert 4D LSM data to a series of 3D data compatible to MultiVolume Explorer
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** With a converted series of 3D data, MultiVolume explorer offered a basic analysis tool for hyperspectral data.
 +
** Label statistics or segmentation need to be added in the future
 +
 
 +
* Registration
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** Basic registration algorithms in Slicer worked well on linear registration between 3D SIM and a cropped and dimension reduced 4D LSM data.
 +
** Detecting corresponding regions of 3D SIM in 4D LSM data needs to be developed in the future.
 +
 
 +
* Segmentation
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** Watershed segmentation on 3D hi-res image data (WASP) was not successful.
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** Editor/Segmentation Editor worked good on slice-by-slice segmentation
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** Will investigate more on 3D segmentation capability of Slicer with possible collaboration with other groups.
  
==Illustrations==
 
  
  
https://www.slicer.org/img/Slicer4Announcement-HiRes.png
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|}
  
<embedvideo service="youtube">https://www.youtube.com/watch?v=MKLWzD0PiIc</embedvideo>
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==Illustrations==
  
 
==Background and References==
 
==Background and References==
 
<!-- Use this space for information that may help people better understand your project, like links to papers, source code, or data -->
 
<!-- Use this space for information that may help people better understand your project, like links to papers, source code, or data -->

Revision as of 14:51, 12 June 2017

Home < Project Week 25 < Multimodal:


Back to Projects List


Key Investigators

  • Guido Gerig (NYU Tandon School of Engineering)
  • Sungmin Hong (NYU Tandon School of Engineering)


Project Description

Objective Approach and Plan Progress and Next Steps

3D/4D Ophthalmology Image Anaylsis Framework

  • Read 4D hyperspectral data
  • Viewer and interactor for 3D hi-res image data and 4D hyperspectral data
  • Co-registration between 3D hi-res data and 4D hyperspectral data
  • Cell segmentation in 3D hi-res data
  • Statistics of cells (possibly location, size, distribution)
  • Plot of spectra of selected cells or a region-of-interest
  • Review existing modules in 3D Slicer
    • Review existing modules for 4D data viewer, such as, multi-volume viewer extension
    • Try existing segmentation modules in Slicer to see if they can work on SIM data
    • Review existing modules for cell statistics after segmentation
  • Implementation/Integration
    • Implement/integrate 4D hyperspectral data viewer to show image and spectral information.
    • Integrate registration functionality for co-registration between 3D hi-res data and 4D hyperspectral data at image level
    • Integrate user-initialized level set segmentation for cell segmentation or EM segmentation module
    • Implement a viewer and an interactor for cell statistics
  • User Manual
    • Create an user manual to comprehend a overview of an extension
    • Guide users to different extensions in a algorithmic flow chart if there are any desired functions (registration, segmentation, or etc.) which are already implemented in existing modules.
  • Hyperspectral Analysis
    • Implemented a module to convert 4D LSM data to a series of 3D data compatible to MultiVolume Explorer
    • With a converted series of 3D data, MultiVolume explorer offered a basic analysis tool for hyperspectral data.
    • Label statistics or segmentation need to be added in the future
  • Registration
    • Basic registration algorithms in Slicer worked well on linear registration between 3D SIM and a cropped and dimension reduced 4D LSM data.
    • Detecting corresponding regions of 3D SIM in 4D LSM data needs to be developed in the future.
  • Segmentation
    • Watershed segmentation on 3D hi-res image data (WASP) was not successful.
    • Editor/Segmentation Editor worked good on slice-by-slice segmentation
    • Will investigate more on 3D segmentation capability of Slicer with possible collaboration with other groups.


Illustrations

Background and References