Real-time Interactive Tractography Analysis for Multimodal Brain Visualization Tool: MultiXplore

被引:0
作者
Bakhshmand, Saeed M. [1 ]
de Ribaupierre, Sandrine [2 ]
Eagleson, Roy [3 ]
机构
[1] Western Univ, Biomed Engn Grad Program, London, ON, Canada
[2] Western Univ, Dept Clin Neurol Sci, London, ON, Canada
[3] Western Univ, Dept Elect & Comp Engn, London, ON, Canada
来源
MEDICAL IMAGING 2017: IMAGE-GUIDED PROCEDURES, ROBOTIC INTERVENTIONS, AND MODELING | 2017年 / 10135卷
基金
加拿大自然科学与工程研究理事会;
关键词
Diffusion Tensor Imaging; functional MRI; Multimodal; Interactive Visualization; Fiber Tractography; Collision Detection; DIFFUSION;
D O I
10.1117/12.2253907
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Most debilitating neurological disorders can have anatomical origins. Yet unlike other body organs, the anatomy alone cannot easily provide an understanding of brain functionality. In fact, addressing the challenge of linking structural and functional connectivity remains in the frontiers of neuroscience. Aggregating multimodal neuroimaging datasets may be critical for developing theories that span brain functionality, global neuroanatomy and internal microstructures. Functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) are main such techniques that are employed to investigate the brain under normal and pathological conditions. FMRI records blood oxygenation level of the grey matter (GM), whereas DTI is able to reveal the underlying structure of the white matter (WM). Brain global activity is assumed to be an integration of GM functional hubs and WM neural pathways that serve to connect them. In this study we developed and evaluated a two-phase algorithm. This algorithm is employed in a 3D interactive connectivity visualization framework and helps to accelerate clustering of virtual neural pathways. In this paper, we will detail an algorithm that makes use of an index-based membership array formed for a whole brain tractography file and corresponding parcellated brain atlas. Next, we demonstrate efficiency of the algorithm by measuring required times for extracting a variety of fiber clusters, which are chosen in such a way to resemble all sizes probable output data files that algorithm will generate. The proposed algorithm facilitates real-time visual inspection of neuroimaging data to further the discovery in structure-function relationship of the brain networks.
引用
收藏
页数:10
相关论文
共 19 条
  • [1] Bakhshmand S. M., 2016, ORG HUM BRAIN MAPP A
  • [2] 3D interactive tractography-informed resting-state fMRI connectivity
    Chamberland, Maxime
    Bernier, Michael
    Fortin, David
    Whittingstall, Kevin
    Descoteaux, Maxime
    [J]. FRONTIERS IN NEUROSCIENCE, 2015, 9
  • [3] Real-time multi-peak tractography for instantaneous connectivity display
    Chamberland, Maxime
    Whittingstall, Kevin
    Fortin, David
    Mathieu, David
    Descoteaux, Maxime
    [J]. FRONTIERS IN NEUROINFORMATICS, 2014, 8
  • [4] Eichelbaum S., 2010, VMV, P155, DOI DOI 10.2312/PE/VMV/VMV10/155-162
  • [5] Farhat N., 2015, IMAGE GUIDED NEUROSU
  • [6] QUANTITATIVE MEASUREMENT OF REGIONAL CEREBRAL BLOOD-FLOW AND OXYGEN-METABOLISM IN MAN USING O-15 AND POSITRON EMISSION TOMOGRAPHY - THEORY, PROCEDURE, AND NORMAL VALUES
    FRACKOWIAK, RSJ
    LENZI, GL
    JONES, T
    HEATHER, JD
    [J]. JOURNAL OF COMPUTER ASSISTED TOMOGRAPHY, 1980, 4 (06) : 727 - 736
  • [7] Resting State fMRI-guided Fiber Clustering: Methods and Applications
    Ge, Bao
    Guo, Lei
    Zhang, Tuo
    Hu, Xintao
    Han, Junwei
    Liu, Tianming
    [J]. NEUROINFORMATICS, 2013, 11 (01) : 119 - 133
  • [8] MAGNETOENCEPHALOGRAPHY - THEORY, INSTRUMENTATION, AND APPLICATIONS TO NONINVASIVE STUDIES OF THE WORKING HUMAN BRAIN
    HAMALAINEN, M
    HARI, R
    ILMONIEMI, RJ
    KNUUTILA, J
    LOUNASMAA, OV
    [J]. REVIEWS OF MODERN PHYSICS, 1993, 65 (02) : 413 - 497
  • [9] MR IMAGING OF INTRAVOXEL INCOHERENT MOTIONS - APPLICATION TO DIFFUSION AND PERFUSION IN NEUROLOGIC DISORDERS
    LEBIHAN, D
    BRETON, E
    LALLEMAND, D
    GRENIER, P
    CABANIS, E
    LAVALJEANTET, M
    [J]. RADIOLOGY, 1986, 161 (02) : 401 - 407
  • [10] Detecting Brain State Changes via Fiber-Centered Functional Connectivity Analysis
    Li, Xiang
    Lim, Chulwoo
    Li, Kaiming
    Guo, Lei
    Liu, Tianming
    [J]. NEUROINFORMATICS, 2013, 11 (02) : 193 - 210