#introduction To fill in my profile tags, a thread:

#TrakEM2 open source software mostly for #connectomics, and supports manual and automatically montaging and aligning overlapping 2D image tiles (with #SIFT features and rigid or elastic transformation models), and reconstructing by painting volumes or tracing branched neuronal arbors neurons plus synapses to map a #connectome from #vEM (volume electron microscopy).

See: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0038011

Git repository at: https://github.com/trakem2/

TrakEM2 Software for Neural Circuit Reconstruction

A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For model systems such as Drosophila and C. elegans, the limiting step is no longer the acquisition of imagery but the extraction of the circuit from images. For this purpose, we designed a software application, TrakEM2, that addresses the systematic reconstruction of neuronal circuits from large electron microscopical and optical image volumes. We address the challenges of image volume composition from individual, deformed images; of the reconstruction of neuronal arbors and annotation of synapses with fast manual and semi-automatic methods; and the management of large collections of both images and annotations. The output is a neural circuit of 3d arbors and synapses, encoded in NeuroML and other formats, ready for analysis.

#TrakEM2 runs as a plugin of #FijiSc https://fiji.sc/ and in fact motivated the creation of the #FijiSc software in the first place, to manage its many dependencies and facilitate distribution to the broader #neuroscience community.

#TrakEM2 was founded in 2005, when TB-sized datasets were rare and considered large. Largest dataset I've successfully managed with #TrakEM2 was ~16 TB. For larger volumes see #CATMAID.

For 3D visualization #TrakEM2 uses the 3D Viewer https://imagej.net/plugins/3d-viewer/

Fiji: ImageJ, with "Batteries Included"

Fiji: A batteries-included distribution of ImageJ.

The web-based open source software #CATMAID was devised as "google maps but for volumes". Documentation at https://catmaid.org and source code at https://github.com/catmaid/CATMAID/

Modern #CATMAID enables hundreds of #neuroscience researchers world wide to collaboratively map neuronal circuits in large datasets limited only by bandwidth and server-side storage to map and analyse a whole brain #connectome.

See the #Drosophila larval CNS at the #VirtualFlyBrain server: https://l1em.catmaid.virtualflybrain.org/?pid=1&zp=108250&yp=82961.59999999999&xp=54210.799999999996&tool=tracingtool&sid0=1&s0=2.4999999999999996&help=true&layout=h(XY,%20%7B%20type:%20%22neuron-search%22,%20id:%20%22neuron-search-1%22,%20options:%20%7B%22annotation-name%22:%20%22papers%22%7D%7D,%200.6)

Welcome to CATMAID — CATMAID 2021.12.21 documentation

The Collaborative Annotation Toolkit for Massive Amounts of Image Data. Used for image viewing, neuron reconstruction, ontology based annotations and more.