Fetal cortical surface atlas parcellation based on growth patterns

  • Authors
  • Xia J, Wang F, Benkarim O, Sanroma G, Piella G, González-Ballester MA, Hahner N, Eixarch E, Zhang C, Shen D, Shen D, Li G.
  • UPF authors
  • PIELLA FENOY, GEMA; GONZALEZ BALLESTER, MIGUEL ANGEL; ZHANG ., CHONG; SANROMA GÜELL, GERARD; BENKARIM ., MOHAMED OUALID;
  • Type
  • Scholarly articles
  • Journal títle
  • Human Brain Mapping
  • Publication year
  • 2019
  • Volume
  • 40
  • Number
  • 13
  • Pages
  • 3881-3899
  • ISSN
  • 1065-9471
  • Publication State
  • Published
  • Abstract
  • apos; growth trajectories in relation to a set of reference points. Then, we nonlinearly fuse these two similarity matrices into a single one, which can better capture both their common and complementary information than by simply averaging them. Finally, based on this fused similarity matrix, we perform spectral clustering to divide the fetal cortical surface atlases into distinct regions. By applying our method on 25 normal fetuses from 26 to 29 gestational weeks, we construct age¿specific fetal cortical surface atlases equipped with biologically meaningful parcellation maps based on cortical growth patterns. Importantly, our generated parcellation maps reveal spatially contiguous, hierarchical and bilaterally relatively symmetric patterns of fetal cortical surface development.
  • Complete citation
  • Xia J, Wang F, Benkarim O, Sanroma G, Piella G, González-Ballester MA, Hahner N, Eixarch E, Zhang C, Shen D, Shen D, Li G.. Fetal cortical surface atlas parcellation based on growth patterns. Human Brain Mapping 2019; 40(13): 3881-3899.
Bibliometric indicators
  • 6 times cited Scopus
  • 3 times cited WOS
  • Índex Scimago de 2.216(2019)