Linux

NeuroGPS-Tree is a workflow developed to reconstruct a neuronal population from a dense, large-scale data set. NeuroGPS-Tree is suitable for processing image stacks acquired by different image modalities.

ClearCL is a Multi-backend Java Object Oriented Facade API for OpenCL.

OpenCL libraries come and go in Java, some are great but then one day the lead developper goes on to greener pastures and you are left with code that needs to be rewritten to take advantage of a new up-to-date library with better support. Maybe a particular library has a bug or does not support the function you need? or it does not give you access to the underlying native pointers, making difficult to process large buffers/images or interoperate with hardware? or maybe it just does not support your exotic OS of choice. To protect your code from complete rewrites ClearCL offers a very clean and complete API to write your code against. Changing backend requires just changing one line of code.

MTrack is a tool, which detects, tracks, and measures the behavior of fluorescently labeled microtubules imaged by TIRF (total internal reflection fluorescence) microscopy. In such an in vitro reconstitution approach, stabilized, non-dynamic microtubule seeds serve as nucleation points for dynamically growing microtubules.

MTrack is a bi-modular tool. The first module detects and tracks the growing microtubule ends and creates trajectories. The second module uses these trajectories to fit models of dynamic behavior (polymerization and depolymerization velocities, catastrophe and rescue frequencies). It also computes statistics such as length and lifetime distributions when analyzing more than one movie (batch mode).

Calculates and corrects for lens-distortion models including chromatic abberation from confocal stacks.

SliceMap

Whole brain tissue slices are commonly used in neurobiological research for analyzing pathological features in an anatomically defined manner. However, since many pathologies are expressed in specific regions of the brain, it is necessary to have an annotation of the regions in the brain slices. Such an annotation can be done by manual delineation, as done most often, or by an automated region annotation tool.

SliceMap is a FIJI/ImageJ plugin for automated brain region annotation of fluorescent brain slices. The plugin uses a reference library of pre-annotated brain slices (the brain region templates) to annotate brain regions of unknown samples. To perform the region annotation, SliceMap registers the reference slices to the sample slice (using elastic registration plugin BUnwarpJ) and uses the resulting image transformations to morph the template regions towards the anatomical brain regions of the sample. The resulting brain regions are saved as FIJI/ImageJ ROI’s (Regions Of Interest) as a single zip-file for each sample slice.

More information can also be found in "SliceMap: an algorithm for automated brain region annotation", Michaël Barbier, Astrid Bottelbergs, Rony Nuydens, Andreas Ebneth, Winnok H De Vos, Bioinformatics, btx658, https://doi.org/10.1093/bioinformatics/btx658