Fluorescence microscopy

Colocalization Colormap –an ImageJ Plugin for the Quantification and Visualization of Colocalized Signals

This ImageJ plugin implements the Jaskolski's algorithm (Jaskolski et al. 2005). It creates a pseudo-color map of correlations between pairs of corresponding pixels in two original input images. With it one can quantitativly visualize colocalization.

Big-FISH is a python package for the analysis of smFISH images (2D/3D). It includes various methods to analyze microscopy images, such spot detection and segmentation of cells and nuclei.

EPySeg is a package for segmenting 2D epithelial tissues. EPySeg also ships with a graphical user interface that allows for building, training and running deep learning models.

Training can be done with or without data augmentation (2D-xy and 3D-xyz data augmentation are supported). EPySeg relies on the segmentation_models library. EPySeg source code is available here. Cloud version available here.

Fast4DReg is a Fiji macro for drift correction for 2D and 3D video and is able to correct drift in all x-, y- and/or z-directions. Fast4DReg creates intensity projections along both axes and estimates their drift using cross-correlation based drift correction, and then translates the video frame by frame. Additionally, Fast4DReg can be used for alignment multi-channel 2D or 3D images which is particularly useful for instruments that suffer from a misalignment of channels.

Spine Analyzer allows to semi-automatically segment dendritic spines in 3D+t images and to measure their volumes and the intensities of the signal within in different channels over time.