Automated 3D stitching of axon segments across multiple brain sections
Presenting author:
New viral vectors make it now possible to stain the axonal arborization of isolated long-range projection neurons. While large high-end whole-brain scanning platforms are being developed, most labs rely on Neurolucida (MBF Bioscience) or similar equipment for reconstruction and measurement from serial brain sections. However, axon fragments 3D-traced with Neurolucida need to be manually aligned and stitched across sections, a task that is more time-consuming than the tracing itself. Here, we present a pipeline to semi-automate this process:
1. A version of the Dercksen et al. (2009, doi 10.1109/ISBI.2009.5193216) algorithm is used to align high endings of fragments to low endings of fragments in the adjacent section.
2. This resulting set of putative links are loaded into a visual stitching tool, in which about 5 to 10 putative links per set of adjacent sections are confirmed as a 'stitch'.
3. With the confirmed links as constraints, step 1 is repeated, resulting in a final set of putative links that can be confirmed as a group.
4. In the visual stitching tool, unpaired fragments are confirmed as 'terminals', or the erroneous classification 'low ending' or 'high ending' is corrected.
Steps 1 and 3 are implemented as python and C code, whereas steps 2 and 4 are performed in an interactive webpage. The pipeline will be made available through the NeuronsReunited project website https://neuroinformatics.nl/NeuronsReunited/stitching.
Supported by FLAG-ERA grant NeuronsReunited, by NWO (680-91-318) and MICINN-AEI (PCI2019-111900-2). Rembrandt Bakker is supported by EU H2020 Research and Innovation Programme under grant agreement 945539 (HBP SGA3).
1. A version of the Dercksen et al. (2009, doi 10.1109/ISBI.2009.5193216) algorithm is used to align high endings of fragments to low endings of fragments in the adjacent section.
2. This resulting set of putative links are loaded into a visual stitching tool, in which about 5 to 10 putative links per set of adjacent sections are confirmed as a 'stitch'.
3. With the confirmed links as constraints, step 1 is repeated, resulting in a final set of putative links that can be confirmed as a group.
4. In the visual stitching tool, unpaired fragments are confirmed as 'terminals', or the erroneous classification 'low ending' or 'high ending' is corrected.
Steps 1 and 3 are implemented as python and C code, whereas steps 2 and 4 are performed in an interactive webpage. The pipeline will be made available through the NeuronsReunited project website https://neuroinformatics.nl/NeuronsReunited/stitching.
Supported by FLAG-ERA grant NeuronsReunited, by NWO (680-91-318) and MICINN-AEI (PCI2019-111900-2). Rembrandt Bakker is supported by EU H2020 Research and Innovation Programme under grant agreement 945539 (HBP SGA3).