Fetal cortical parcellation based on growth patterns

  • Authors
  • Xia J, Zhang C, Wang F, Benkarim OM, Sanroma G, Piella G, Gonzalez-Ballester MA, Hahner N, Eixarch E, Shen D, Li G.
  • UPF authors
  • PIELLA FENOY, GEMA; GONZALEZ BALLESTER, MIGUEL ANGEL;
  • Type
  • Scholarly articles
  • Journal títle
  • Proceedings of the IEEE International Symposium on Biomedical Imaging
  • Publication year
  • 2018
  • Pages
  • 0-0
  • ISSN
  • 1945-8452
  • Publication State
  • Published
  • Abstract
  • apos; growth trajectories in relation to those of reference points. Then, we nonlinearly fuse these two similarity matrices into a single one, which can better captures both their common and complementary information than by simply averaging them. Finally, based on this fused matrix, we perform spectral clustering to divide fetal cortical surfaces into distinct regions. We have applied our method on 25 normal fetuses from 26 to 29 gestational weeks and generated biologically meaningful parcellations.
  • Complete citation
  • Xia J, Zhang C, Wang F, Benkarim OM, Sanroma G, Piella G, Gonzalez-Ballester MA, Hahner N, Eixarch E, Shen D, Li G.. Fetal cortical parcellation based on growth patterns. Proceedings of the IEEE International Symposium on Biomedical Imaging 2018; ( ).
Bibliometric indicators
  • 2 times cited Scopus