Project Week 25/Multimodal:

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Key Investigators

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

Project Description

Project details can downloaded here as pptx or [File:File:Gerig-Slicer-6-26-2017-final.pdf | pdf]

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

SIM-LSM-granules-for-Wiki.png

Background and References