Image analysis at LMU

 

Intensity within a region of interest (tissue, cells, organelles) can be measured using various tools. Fiji offers a basic tool set for 2D-image processing while Imaris can be used to extract advanced 3D statistics. Should you have vast amounts of data, Cell Profiler can be trained to analyze your data for you.

See more on LMU Wiki.

 

Fiji offers a basic tool set for 2D-image cell counting while Imaris can be used to count cells in 3D / 4D images. Should you have vast amounts of data, Cell Profiler can be trained to count your cells for you.
 

See more on LMU Wiki.

 

 

Imaris can be used to create a fancy 3D image and/or video of your object of interest. These 3D renderings can be also used to study object morphology.

See more on LMU Wiki.

 

Neural Morphology can be analyzed with Imaris filament tracer or NeuronStudio. We can calculate the amount of branching points and the width of the branches.

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Imaris and Neuronstudio can be used to count and characterize spines, though image quality has to be exceptional for the analysis to work reliably.  Data should be aqcuired with our high-end confocal microscopes and the images should be deconcolved before the analysis.

See more on LMU Wiki.

 

Imaris can be used to perform various ‘colocalization’ measurements.  Colocalization tool can be used to extract Mander’s and Pearson’s coefficients. Alternatively we can measure how spots colocalize with other spots on 3D space.

See more on LMU Wiki.

 

Imaris can be used to track objects over time.  Image quality has to be pretty good and the time resolution must be sufficient for the toolset to work reliably.
 

See more on LMU Wiki.

 

 

AutoQuant and Microvolution can be used to perform 4D deconvolution to improve image quality and reduce noise. The data must have sufficient sampling for deconvolution to work properly.  Both software have also batch processing capabilities.

See more on LMU Wiki.

 

Should you need something not listed on this page, we can likely come up with something – or if needed, program you a custom solution.

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Imaris can be used to quantify distances between structures.  For example we can measure how close vesicles are to nucleus or cell membrane if the structures of interest are stained well. This allows us to study the distribution of structures as function of distance to whatever we deem interesting.  Similarly we can quantify distances between cells and the the distance between cells and tissue border.

See more on LMU Wiki.

 

We can help people with statistics, providing people information about existing methods and their applicability to the data in question. If you do not know whether ANOVA can cannot be applied and/or what multiple comparisons problem means we are here to help.

See more on LMU Wiki.