Hello all,
My goal is to more clearly demonstrate protein localization at the tips of structures (microvilli) which project upwards from the cell's apical surface through many z-slices. A standard maximum intensity projection (as well as any individual z-slice) just shows bright puncta of accumulation, but it is not obvious that this localization is at microvilli tips - it could be from localization in the body, protein aggregation, etc...
To create an orthogonal view, I used ImageJ: "Image > Stacks > Orthogonal Views". However, the result this gave me is very low resolution. You can only see a blurry layer of green (the protein) on top of a blurry layer of red (phalloidin-labeled microvilli). The image I'm talking about is attached to the question. I was really hoping that the orthogonal view would more clearly show the microvilli structures.
The original z-stack is 13 slices, and each slice overlaps only slightly with the previous. I suppose taking a larger z-stack with more slices would improve resolution, as well as decreasing the inter-slice distance. But is there anything else I can do to improve the orthogonal view (preferably in processing rather than image acquisition)? Are there any other image-processing softwares, add-ons, or techniques which I could use to better demonstrate this localization?
Any feedback is very welcome. Thanks!
1.I would say ImageJ since it is free... not a fan but their contrast enhancement is better ...
2.Adobe they have a cloud (depends on your data too !!)
3.Matlab (i have not used the function) http://www.mathworks.com/help/matlab/ref/slice.html
It would be difficult to improve image quality without working on image acquisition... The strongest problem in your study seems to be the z-resolution, but it is difficult to improve. Maybe using advanced imaging techniques such as PALM or STORM may help, but I do not know if it is suited for colocalisation analysis.
Another way of improvement can be to apply "deconvolution" algorithm. This increases the resolution of the image using assumptions on the point spread function of the microscope. Maybe this would help for colocalisation. Classical software for this is "Huygens", but others may be found.
https://svi.nl/DeConvolution
Hey - I just wanted to follow up with you both - unfortunately, I wasn't able to try all of your suggestions, but I was able to get a decent improvement in resolution (see attached).
It turns out the biggest problem was my original image acquisition (the one thing I didn't want to go go back and do!) - this new orthogonal projection is based on 4X as many z-slices, and a greater overlap between slices. Luckily, I was still able to do this on a confocal microscope. The file came off of the microscope in a ".LSM" file, so I was unable to deconvolve it, although I looked into that route as well. Thanks again!
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