AUTOMATIC CORTICAL SURFACE PARCELLATION BASED ON FIBER DENSITY INFORMATION

被引:11
|
作者
Zhang, Degang [1 ,3 ,4 ]
Guo, Lei [1 ]
Li, Gang [1 ]
Nie, Jingxin [1 ]
Deng, Fan [2 ,3 ]
Li, Kaiming [1 ,2 ,3 ]
Hu, Xintao [1 ]
Zhang, Tuo [1 ]
Jiang, Xi [1 ]
Zhu, Dajiang [2 ,3 ]
Zhao, Qun [3 ,4 ]
Liu, Tianming [2 ,3 ]
机构
[1] Northwestern Polytech Univ, Sch Automat, Xian 710072, Peoples R China
[2] Univ Georgia, Dept Comp Sci, Athens, GA 30602 USA
[3] Univ Georgia, Bioimaging Res Ctr, Athens, GA 30602 USA
[4] Univ Georgia, Dept Phys, Athens, GA 30602 USA
关键词
Cortical surface parcellation; fiber density; structure network; CONNECTIVITY-BASED PARCELLATION; HUMAN THALAMUS; CORTEX; REGISTRATION; REGIONS; FLOW; MRI;
D O I
10.1109/ISBI.2010.5490193
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
It is widely believed that the structural connectivity of a brain region largely determines its function. High resolution Diffusion Tensor Imaging (DTI) is now able to image the axonal fibers in vivo and the DTI tractography result provides rich connectivity information. In this paper, a novel method is proposed to employ fiber density information for automatic cortical parcellation based on the premise that fibers connecting to the same cortical region should be within the same functional brain network and their aggregation on the cortex can define a functionally coherent region. This method consists of three steps. Firstly, the fiber density is calculated on the cortical surface. Secondly, a flow field is obtained by calculating the fiber density gradient and a flow field tracking method is utilized for cortical parcellation. Finally, an atlas-based warping method is used to label the parcellated regions. Our method was applied to parcellate and label the cortical surfaces of eight healthy brain DTI images, and interesting results are obtained. In addition, the labeled regions are used as ROIs to construct structural networks for different brains, and the graph properties of these networks are measured.
引用
收藏
页码:1133 / 1136
页数:4
相关论文
共 50 条
  • [1] CORTICAL SURFACE PARCELLATION BASED ON GRAPH REPRESENTATION OF SHORT FIBER BUNDLE CONNECTIONS
    Silva, Felipe
    Guevara, Miguel
    Poupon, Cyril
    Mangin, Jean-Francois
    Hernandez, Cecilia
    Guevara, Pamela
    [J]. 2019 IEEE 16TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2019), 2019, : 1479 - 1482
  • [2] A new cortical surface parcellation model and its automatic implementation
    Clouchoux, Cedric
    Coulon, Olivier
    Anton, Jean-Luc
    Mangin, Jean-Francois
    Regis, Jean
    [J]. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2006, PT 2, 2006, 4191 : 193 - 200
  • [3] Automatic Cortical Sulcal Parcellation Based on Surface Principal Direction Flow Field Tracking
    Li, Gang
    Guo, Lei
    Nie, Jingxin
    Liu, Tianming
    [J]. INFORMATION PROCESSING IN MEDICAL IMAGING, PROCEEDINGS, 2009, 5636 : 202 - +
  • [4] Automatic cortical sulcal parcellation based on surface principal direction flow field tracking
    Li, Gang
    Guo, Lei
    Nie, Jingxin
    Liu, Tianming
    [J]. NEUROIMAGE, 2009, 46 (04) : 923 - 937
  • [5] Cortical surface parcellation based on intra-subject white matter fiber clustering
    Lopez-Lopez, Narciso
    Vazquez, Andrea
    Poupon, Cyril
    Mangin, Jean-Francois
    Guevara, Pamela
    [J]. 2019 IEEE CHILEAN CONFERENCE ON ELECTRICAL, ELECTRONICS ENGINEERING, INFORMATION AND COMMUNICATION TECHNOLOGIES (CHILECON), 2019,
  • [6] Automatic Parcellation of Longitudinal Cortical Surfaces
    Alassaf, Manal H.
    Hahn, James K.
    [J]. MEDICAL IMAGING 2015: IMAGE PROCESSING, 2015, 9413
  • [7] Group-Wise Cortical Surface Parcellation Based on Inter-Subject Fiber Clustering
    Vergara, Christopher
    Silva, Felipe
    Huerta, Isaias
    Lopez-Lopez, Narciso
    Vazquez, Andrea
    Houenou, Josselin
    Poupon, Cyril
    Mangin, Jean-Francois
    Hernandez, Cecilia
    Guevara, Pamela
    [J]. 2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC), 2021, : 2655 - 2659
  • [8] A sub plus cortical fMRI-based surface parcellation
    Lewis, John D.
    Bezgin, Gleb
    Fonov, Vladimir S.
    Collins, D. Louis
    Evans, Alan C.
    [J]. HUMAN BRAIN MAPPING, 2022, 43 (02) : 616 - 632
  • [9] Fetal cortical surface atlas parcellation based on growth patterns
    Xia, Jing
    Wang, Fan
    Benkarim, Oualid M.
    Sanroma, Gerard
    Piella, Gemma
    Gonzalez Ballester, Miguel A.
    Hahner, Nadine
    Eixarch, Elisenda
    Zhang, Caiming
    Shen, Dinggang
    Li, Gang
    [J]. HUMAN BRAIN MAPPING, 2019, 40 (13) : 3881 - 3899
  • [10] Functional parcellation of the neonatal cortical surface
    Myers, Michael J.
    Labonte, Alyssa K.
    Gordon, Evan M.
    Laumann, Timothy O.
    Tu, Jiaxin C.
    Wheelock, Muriah D.
    Nielsen, Ashley N.
    Schwarzlose, Rebecca F.
    Camacho, M. Catalina
    Alexopoulos, Dimitrios
    Warner, Barbara B.
    Raghuraman, Nandini
    Luby, Joan L.
    Barch, Deanna M.
    Fair, Damien A.
    Petersen, Steven E.
    Rogers, Cynthia E.
    Smyser, Christopher D.
    Sylvester, Chad M.
    [J]. CEREBRAL CORTEX, 2024, 34 (02)