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Distance networks for morphological profiling and characterization of DICCCOL landmarks

  • Yue Yuan
  • , Hanbo Chen
  • , Jianfeng Lu
  • , Tuo Zhang
  • , Tianming Liu
  • Nanjing University of Science and Technology
  • University of Georgia

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In recent works, 358 cortical landmarks named Dense Individualized Common Connectivity based Cortical Landmarks (DICCCOLs) were identified. Instead of whole-brain parcellation into sub-units, it identified the common brain regions that preserve consistent structural connectivity profile based diffusion tensor imaging (DTI). However, since the DICCCOL system was developed based on connectivity patterns only, morphological and geometric features were not used. Thus, in this paper, we constructed distance networks based on both geodesic distance and Euclidean distance to morphologically profile and characterize DICCCOL landmarks. Based on the distance network derived from 10 templates subjects with DICCCOL, we evaluated the anatomic consistency of each DICCCOL, identified reliable/unreliable DICCCOLs, and modeled the distance network of DICCCOLs. Our results suggested that the most relative consistent connections are long distance connections. Also, both of the distance measurements gave consistent observations and worked well in identifying anatomical consistent and inconsistent DICCCOLs. In the future, distance networks can be potentially applied as a complementary metric to improve the prediction accuracy of DICCCOLs or other ROIs defined on cortical surface.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI 2015 - 18th International Conference, Proceedings
EditorsJoachim Hornegger, Alejandro F. Frangi, William M. Wells, Alejandro F. Frangi, Nassir Navab, Joachim Hornegger, Nassir Navab, William M. Wells, William M. Wells, Alejandro F. Frangi, Joachim Hornegger, Nassir Navab
PublisherSpringer Verlag
Pages380-387
Number of pages8
ISBN (Print)9783319245706, 9783319245706, 9783319245706
DOIs
StatePublished - 2015
Event18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015 - Munich, Germany
Duration: 5 Oct 20159 Oct 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9350
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2015
Country/TerritoryGermany
CityMunich
Period5/10/159/10/15

Keywords

  • Cortical landmark
  • DICCCOL
  • Euclidean distance
  • Geodesic distance
  • ROIs

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