Name
Abstract | ||
|---|---|---|
Zigzag persistent homology techniques are applied to the processing of actual neuronal images.These algorithms allow us to recognize dendrites, which cross in space.Our methods have been implemented as a Fiji/ImageJ plugin, which is in production.The plugin is applicable to different kinds of neuronal images. We apply the ideas of zigzag persistence to determine the objects of interest in stacks of neuronal images, locating and marking different dendrites. In particular, this allows us to recognize some 3D properties of the objects, distinguishing dendrites that cross, but not intersect, in the ambient space. The algorithms are implemented in a Fiji/ImageJ plugin, usable on two different kinds of images. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1016/j.patrec.2015.05.010 | Pattern Recognition Letters |
Keywords | Field | DocType |
Neural images,Dendrite reconstruction,Homology, | Ambient space,USable,Computer vision,Pattern recognition,Computer science,Persistent homology,Artificial intelligence,Zigzag,The Intersect | Journal |
Volume | Issue | ISSN |
62 | C | 0167-8655 |
Citations | PageRank | References |
3 | 0.50 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gadea Mata | 1 | 14 | 3.57 |
| m morales | 2 | 4 | 1.86 |
| Ana Romero | 3 | 8 | 3.76 |
| J. Rubio | 4 | 202 | 31.12 |