In image processing, it is most of the time necessary to pre-process images through images denoising, removing blurred images, signal stabilisation to counter signal bleaching or irregular illumination, ...
In this section, we introduce you with our pre and post-processing steps and tricks through different examples to produce high quality results.
MIAtecs algorithms
extract a clear signal from raw blurred images
In this raw confocal image, we can observe a plasma membrane protein fused to a GFP tag and clustered in PM nanodomains.
The automated detection of every nanodomains and the extraction of quantitative information requires to clear the background using filters and mathematics.
MIAtecs corrects
signal bleaching in
time lapse sequences
One of the most difficult thing to control in live cell imaging is fluorophores photobleaching.
Indeed, some fluorophores require a high laser power to obtain a good signal/noise ratio. Unfortunatelly, this will result in a signal bleaching.
If the acquisition settings are already optimized, a second solution consists in the post-processing of the dataset to correct the signal along the acquisition.
Raw dataset / Bleach correction
MIAtecs knows how to register highly dynamic objects
Extracting quantitative information from highly dynamic objects in time-lapse sequences can be challenging.
Here, we identified a single CESA 'Donut' particle and registered the full image stack against the first 'Donut' position. In the resulting image sequences, the CESA 'Donut' can be easily visualized and analyzed.
WHAT TOOLS WILL BE USED TO PROVIDE YOU HIGH QUALITY RESULTS?
