Exploring gyral patterns of infant cortical folding based on multi-view curvature information

Dingna Duan, Shunren Xia, Yu Meng, Li Wang, Weili Lin, John H. Gilmore, Dinggang Shen, Gang Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

The human cortical folding is intriguingly complex in its variability and regularity across individuals. Exploring the principal patterns of cortical folding is of great importance for neuroimaging research. The term-born neonates with minimum exposure to the complicated environments are the ideal candidates to mine the postnatal origins of principal cortical folding patterns. In this work, we propose a novel framework to study the gyral patterns of neonatal cortical folding. Specifically, first, we leverage multi-view curvature-derived features to comprehensively characterize the complex and multi-scale nature of cortical folding. Second, for each feature, we build a dissimilarity matrix for measuring the difference of cortical folding between any pair of subjects. Then, we convert these dissimilarity matrices as similarity matrices, and nonlinearly fuse them into a single matrix via a similarity network fusion method. Finally, we apply a hierarchical affinity propagation clustering approach to group subjects into several clusters based on the fused similarity matrix. The proposed framework is generic and can be applied to any cortical region, or even the whole cortical surface. Experiments are carried out on a large dataset with 600+ term-born neonates to mine the principal folding patterns of three representative gyral regions.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer Assisted Intervention − MICCAI 2017 - 20th International Conference, Proceedings
PublisherSpringer Verlag
Pages12-20
Number of pages9
Volume10433 LNCS
ISBN (Print)9783319661810
DOIs
Publication statusPublished - 2017 Jan 1
Externally publishedYes
Event20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017 - Quebec City, Canada
Duration: 2017 Sep 112017 Sep 13

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10433 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017
CountryCanada
CityQuebec City
Period17/9/1117/9/13

Keywords

  • Curvature information
  • Gyral pattern
  • Infant cortical folding

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Duan, D., Xia, S., Meng, Y., Wang, L., Lin, W., Gilmore, J. H., Shen, D., & Li, G. (2017). Exploring gyral patterns of infant cortical folding based on multi-view curvature information. In Medical Image Computing and Computer Assisted Intervention − MICCAI 2017 - 20th International Conference, Proceedings (Vol. 10433 LNCS, pp. 12-20). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10433 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-66182-7_2