Graph-based unsupervised segmentation algorithm for cultured neuronal networks' structure characterization and modeling

Autor: Daniel de Santos-Sierra (1,2), Irene Sendiña-Nadal (1,3), Inmaculada Leyva (1,3), Juan A. Almendral (1,3), Amir Ayali (4), Sarit Anava (4,5), Carmen Sánchez-Ávila (2), Stefano Boccaletti (6,7)

Publikováno v: Cytometry. Part A (Online) 87 (2014): 513–523. doi:10.1002/cyto.a.22591
info:cnr-pdr/source/autori:Daniel de Santos-Sierra (1,2); Irene Sendiña-Nadal (1,3); Inmaculada Leyva (1,3); Juan A. Almendral (1,3); Amir Ayali (4); Sarit Anava (4,5); Carmen Sánchez-Ávila (2); Stefano Boccaletti (6,7)/titolo:Graph-based unsupervised segmentation algorithm for cultured neuronal networks' structure characterization and modeling/doi:10.1002%2Fcyto.a.22591/rivista:Cytometry. Part A (Online)/anno:2014/pagina_da:513/pagina_a:523/intervallo_pagine:513–523/volume:87

Large scale phase-contrast images taken at high resolution through the life of a cultured neuronal network are analyzed by a graph-based unsupervised segmentation algorithm with a very low computational cost, scaling linearly with the image size. The

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid_dedup__::27be46c74427ac3c8c9f90d6f4d663b2
https://pubmed.ncbi.nlm.nih.gov/25393432