Measure cell volume over time

Type
Author
Imaris Tutorials, Christoph Moehl
Requires
Interaction Level
License/Openness
Description
The workflow describes a solution to measure growth of cells in 3D. The sample dataset (part of the github repository) contains 2-Photon images of neurons. The neurons are imaged in 3D at two timeframes.To be able to measure significant differences in cell volume, the time gap of the frames is huge (ca. 30 min) and the animal was removed in the waiting phase. Thus, there is significant shift between the frames that has to be corrected before cell detection and tracking. The worflow consists of following steps: 1. Import of single tiff slices [imageJ macro] 2. Organizing the data in a 4D time series with 2 time frames [imageJ macro] 3. Correction of shift between the time frames by rigid registration [imagJ macro] 4. Bleaching correction [imageJ macro] 5. Export of preprocessed image data in ics/ids format [imageJ macro] 6. Import of ics/ids data to Imaris [Imaris] 7. Cell object detection as "Imaris Surface Object" [Imaris] 8. Tracking cell objects over time [Imaris] 9. Split Tracks (use Imaris XT extension "Split Tracks") to generate single cell objects [Imaris] 10. Export the statistics: Select the complete folder, go to the statistics tab and use ‚Full Export’ [Imaris] The prepocessing macro can be referenced here: [![DOI](https://zenodo.org/badge/7683/cmohl2013/registration_and_bleaching_corr…)](http://dx.doi.org/10.5281/zenodo.13167) The sample images were acquired by Cordula Ulbrich (Petzold Group at German Center of Neurodegenerative Disesases (DZNE), Bonn, Germany).
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Last modified
09/12/2017 - 20:02