Free and open source

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.

Crop 2D/3D images with arbitrary box size and orientation(s).

The RotCrop Plugins for ImageJ allow to perform rotated crop of 2D/3D images. In fully manual versions, the crop can be defined based on crop dimensions, crop center, and rotation angle(s) of the crop frame (in 3D, three angles are necessary).

Additional plugins provides an estimate of the rotation based on the gradient vector computed around the crop frame center. The gradient direction is used as vertical direction in the result, making it easier to generate 2D/3D images that are tangent to a surface such as the epidermis of an organ or organism.

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.

A collection of Image Processing and Analysis (IPA) functions used at the Facility for Advanced Imaging and Microscopy (FAIM).

DeXtrusion is a machine learning based python pipeline to detect cell extrusions in epithelial tissues movies. It can also detect cell divisions and SOPs, and can easily be trained to detect other dynamic events.

DeXtrusion takes as input a movie of an epithelium and outputs the spatio-temporal location of cell extrusion events or other event as cell divisions. The movie is discretized into small overlapping rolling windows which are individually classified for event detection by a trained neural network. Results are then put together in event probability map for the whole movie or as spatio-temporal points indicating each event.