Difference between revisions of "2017 Winter Project Week/HyperspectralOpht"

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==Project Description==
 
==Project Description==
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This project aims to offer a tool which makes use of 3D/4D ophthalmology data in different modalities to extract information which can compensate each other for richer analysis.
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3D high resolution data (SIM) displays individual cells with sharp boundaries which are hard to be localized in 4D hyperspectral data (LSM) because of low resolution.
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The tool that we want to provide to users should offer image processing modules, such as, co-registration between SIM and LSM data, segmentation on SIM and mapping the segmentation label from SIM to LSM to analyze spectral information of each cell.
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! style="text-align: left; width:27%" |  Objective
 
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Revision as of 05:22, 3 January 2017

Home < 2017 Winter Project Week < HyperspectralOpht

Key Investigators

  • Sungmin Hong (NYU)
  • Guido Gerig (NYU)

Project Description

This project aims to offer a tool which makes use of 3D/4D ophthalmology data in different modalities to extract information which can compensate each other for richer analysis. 3D high resolution data (SIM) displays individual cells with sharp boundaries which are hard to be localized in 4D hyperspectral data (LSM) because of low resolution. The tool that we want to provide to users should offer image processing modules, such as, co-registration between SIM and LSM data, segmentation on SIM and mapping the segmentation label from SIM to LSM to analyze spectral information of each cell.

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

Background and References