Zigzag persistent homology for processing neuronal images

  1. Mata, G. 1
  2. Morales, M. 2
  3. Romero, A. 1
  4. Rubio, J. 1
  1. 1 Universidad de La Rioja
    info

    Universidad de La Rioja

    Logroño, España

    ROR https://ror.org/0553yr311

  2. 2 Universitat Autònoma de Barcelona
    info

    Universitat Autònoma de Barcelona

    Barcelona, España

    ROR https://ror.org/052g8jq94

Aldizkaria:
Pattern Recognition Letters

ISSN: 0167-8655

Argitalpen urtea: 2015

Alea: 62

Orrialdeak: 55-60

Mota: Artikulua

DOI: 10.1016/J.PATREC.2015.05.010 SCOPUS: 2-s2.0-84936806400 WoS: WOS:000357048400009 GOOGLE SCHOLAR

Beste argitalpen batzuk: Pattern Recognition Letters

Lotura duten proiektuak

Formalización de las matemáticas: aplicaciones en cálculo simbólico y álgebra computacional. Formalization of mathematics. applications to symbolic computation and computer algebra.

2015/00074/001

Laburpena

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. © 2015ElsevierB.V.Allrightsreserved.