A generic framework for the parcellation of the cortical surface into gyri using geodesic Voronoi diagrams

被引:71
作者
Cachia, A [1 ]
Mangin, JF
Rivière, D
Papadopoulos-Orfanos, D
Kherif, F
Bloch, I
Régis, J
机构
[1] CEA, Serv Hosp Frederic Joliot, F-91401 Orsay, France
[2] Serv Neurochirurg Fonct & Stereotax, Marseille, France
[3] ENST, CNRS, U820, Dept Traitement Signal & Images, Paris, France
[4] INSERM, ERM 0205, Imagerie Cerebrale & Psychiat, Orsay, France
[5] Inst Fedaratif Rech, Paris, France
关键词
brain; cortex; MRI; parcellation; gyri; sulci; morphometry;
D O I
10.1016/S1361-8415(03)00031-8
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper we propose a generic automatic approach for the parcellation of the cortical surface into labeled gyri. These gyri are defined from a set of pairs of sulci selected by the user. The selected sulci are first automatically identified in the data, then projected onto the cortical surface. The parcellation stems from two nested Voronoi diagrams computed geodesically to the cortical surface. The first diagram provides the zones of influence of the sulci. The boundary between the two zones of influence of each selected pair of sulci stands for a gyrus seed. A second diagram yields the gyrus parcellation. The distance underlying the Voronoi diagram allows the method to interpolate the gyrus boundaries where the limiting sulci are interrupted. The method is illustrated with 12 different hemispheres. (C) 2003 Elsevier B.V. All rights reserved.
引用
收藏
页码:403 / 416
页数:14
相关论文
共 10 条
  • [1] A Whole Brain Atlas with Sub-parcellation of Cortical Gyri using Resting fMRI
    Joshi, Anand A.
    Choi, Soyoung
    Sonkar, Gaurav
    Chong, Minqi
    Gonzalez-Martinez, Jorge
    Nair, Dileep
    Shattuck, David W.
    Damasio, Hanna
    Leahy, Richard M.
    MEDICAL IMAGING 2017: IMAGE PROCESSING, 2017, 10133
  • [2] Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature
    Destrieux, Christophe
    Fischl, Bruce
    Dale, Anders
    Halgren, Eric
    NEUROIMAGE, 2010, 53 (01) : 1 - 15
  • [3] GeoSP: A parallel method for a cortical surface parcellation based on geodesic distance
    Lopez-Lopez, Narciso
    Vazquez, Andrea
    Poupon, Cyril
    Mangin, Jean-Francois
    Ladra, Susana
    Guevara, Pamela
    42ND ANNUAL INTERNATIONAL CONFERENCES OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY: ENABLING INNOVATIVE TECHNOLOGIES FOR GLOBAL HEALTHCARE EMBC'20, 2020, : 1696 - 1700
  • [4] A Framework for Using Diffusion Weighted Imaging to Improve Cortical Parcellation
    Clarkson, Matthew J.
    Malone, Ian B.
    Modat, Marc
    Leung, Kelvin K.
    Ryan, Natalie
    Alexander, Daniel C.
    Fox, Nick C.
    Ourselin, Sebastien
    MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2010, PT I, 2010, 6361 : 534 - +
  • [5] Parcellation of Infant Surface Atlas Using Developmental Trajectories of Multidimensional Cortical Attributes
    Li, Gang
    Wang, Li
    Gilmore, John H.
    Lin, Weili
    Shen, Dinggang
    MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION, PT III, 2015, 9351 : 543 - 550
  • [6] CORTICAL SURFACE PARCELLATION VIA DMRI USING MUTUAL NEAREST NEIGHBOR CONDITION
    Belaoucha, Brahim
    Clerc, Maureen
    Papadopoulo, Theodore
    2016 IEEE 13TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI), 2016, : 903 - 906
  • [7] From Coarse to Fine-Grained Parcellation of the Cortical Surface Using a Fiber-Bundle Atlas
    Lopez-Lopez, Narciso
    Vazquez, Andrea
    Houenou, Josselin
    Poupon, Cyril
    Mangin, Jean-Francois
    Ladra, Susana
    Guevara, Pamela
    FRONTIERS IN NEUROINFORMATICS, 2020, 14
  • [8] Connectivity-based parcellation of the cortical surface using q-ball imaging
    Guevara, Pamela
    Perrin, Muriel
    Cathier, Pascal
    Cointepas, Yann
    Riviere, Denis
    Poupon, Cyril
    Mangin, Jean-Francois
    2008 IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, VOLS 1-4, 2008, : 903 - 906
  • [9] Automatic cortical surface parcellation in the fetal brain using attention-gated spherical U-net
    You, Sungmin
    Barba, Anette De Leon
    Tamayo, Valeria Cruz
    Yun, Hyuk Jin
    Yang, Edward
    Grant, P. Ellen
    Im, Kiho
    FRONTIERS IN NEUROSCIENCE, 2024, 18
  • [10] Predicting infant cortical surface development using a 4D varifold-based learning framework and local topography-based shape morphing
    Rekik, Islem
    Li, Gang
    Lin, Weili
    Shen, Dinggang
    MEDICAL IMAGE ANALYSIS, 2016, 28 : 1 - 12