• DocumentCode
    3240183
  • Title

    Group-wise consistent sulcal fundi segmentation based on DMRI-derived ODF features

  • Author

    Tuo Zhang ; Hanbo Chen ; Xi Jiang ; Bao Ge ; Lei Guo ; Tianming Liu

  • Author_Institution
    Sch. of Autom., Northwestern Polytech. Univ., Xi´an, China
  • fYear
    2015
  • fDate
    16-19 April 2015
  • Firstpage
    638
  • Lastpage
    641
  • Abstract
    Recently, it has been shown that structural connectivity patterns derived from diffusion MRI (dMRI) can be used for cortical parcellation and segmentation. However, most previous methods were based on diffusion tractography, which is limited in depicting local profiles, e.g., in regions beneath the cortical sulcal fundi. Instead, in this paper, we propose to derive effective features directly from orientation distribution functions (ODFs), which contain rich information about local fiber connection profiles like crossings. Based on these ODFs features, we adopted a multiview spectral clustering method to group-wisely and consistently parcellate the cortical sulcal fundi. Experimental results on the central sulcal fundi are promising, which is further validated by resting state fMRI data mapping.
  • Keywords
    biodiffusion; biomedical MRI; brain; image segmentation; medical image processing; DMRI-derived ODF features; cortical parcellation; cortical sulcal fundi; crossings; dMRI; diffusion MRI; diffusion tractography; fiber connection profiles; group-wise consistent sulcal fundi segmentation; local profiles; multiview spectral clustering method; orientation distribution functions; resting state fMRI data mapping; structural connectivity patterns; Clustering methods; Correlation; Feature extraction; Image color analysis; Imaging; Optical fiber networks; Shape; ODF; Sulcal fundus; segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Biomedical Imaging (ISBI), 2015 IEEE 12th International Symposium on
  • Conference_Location
    New York, NY
  • Type

    conf

  • DOI
    10.1109/ISBI.2015.7163954
  • Filename
    7163954