Commit 0f75ab97 authored by Philipp Schubert's avatar Philipp Schubert
Browse files

updated README.md

parent ee3a0dc6
# SyConn v2
Refactored (still an early stage construction) version of SyConn for automated synaptic connectivity inference based on dense EM segmentation data. For the first version
see 'SyConn' below. Current features:
- introduction of supervoxel and agglomerated supervoxel classes
- added support for (sub-) cellular compartment (spines, axon/dendrite/soma) and cell type classification with [skeleton](https://www.nature.com/articles/nmeth.4206)- and [multiview-based](https://www.biorxiv.org/content/early/2018/07/06/364034) approaches
- cell organelle prediction, extraction and mesh generation
- glia identification and splitting
- generation of connectivity matrix
Documentation
--------------
_in progress_
# SyConn
Synaptic connectivity inference toolkit developed at the Max-Planck-Institute for Medical Research, Heidelberg and
......@@ -11,7 +26,7 @@ To get started, please have a look at our [documentation](https://structuralneur
Publication
-----------
SyConn was published in [Nature Methods](http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.4206.html) on February 27th 2017. If you use parts of this code base in your academic projects, please cite the corresponding publication. <br />
The first version of SyConn (see branch 'dorkenwald2017nm') was published in [Nature Methods](http://www.nature.com/nmeth/journal/vaop/ncurrent/full/nmeth.4206.html) on February 27th 2017. If you use parts of this code base in your academic projects, please cite the corresponding publication. <br />
```
@ARTICLE{SyConn2017,
......
Markdown is supported
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment