NA-MIC Project Weeks
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Key Investigators
- Xiang Chen (Memorial University of Newfoundland)
- Oscar Meruvia-Pastor (Memorial University of Newfoundland)
- Touati Benoukraf (Memorial University of Newfoundland)
Project Description
This is an extension for computing the percentage of colocalization(Spatial overlap between different channels) of Z-stack TIFF images, which developed for category ‘Quantification’.
Objective
- As of now, the computation of my module is a bit slow(when the threshold range for each selected channel is very large), so I’m hoping to get help from slicer experts to make it faster.
Approach and Plan
- Collaborate with Slicer community members during this Project Week.
Updates and Next Steps
- Currently my extension has already implemented the calculation functionality and the current goal is to increase the calculation speed.
- As shown below, The calculation time has been greatly reduced after removing all unnecessary code related to creating the closed surface representations for all segments.
Before:
Now (The calculation time has been shortened to less than 30s):
When the threshold range is set not that so large, the calculation time will be shorter:
Next Steps:
- Convert the volume corresponding to each channel in the ROI to a numpy array.
- Apply thresholding to all numpy array of the volumes within the ROI.
- Detect all intersections among all channels using numpy indexing.
- Count the number of voxels resulting from step 3 and multiply by the volume of one voxel.
Illustrations
Users can threshold the volume rendering of the input Z-stack image in the 3D view window, select the region of interest(ROI) by the bounding box, and get a Venn diagram that shows the critical metric of colocalization’s percentage. Extension ScreenShots
