Diffusion MRI visualization

被引:13
|
作者
Schultz, Thomas [1 ,2 ]
Vilanova, Anna [3 ]
机构
[1] Bonn Aachen Int Ctr Informat Technol, Bonn, Germany
[2] Univ Bonn, Dept Comp Sci, Bonn, Germany
[3] Delft Univ Technol, Dept Elect Engn Math & Comp Sci EEMCS, Delft, Netherlands
关键词
diffusion MRI; diffusion tensor; tractography; visualization; WHITE-MATTER FIBERS; TENSOR MRI; TRACTOGRAPHY; BRAIN; UNCERTAINTY; CONNECTIVITY; ORIENTATION; TRACKING; TISSUES; DENSITY;
D O I
10.1002/nbm.3902
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
Modern diffusion magnetic resonance imaging (dMRI) acquires intricate volume datasets and biological meaning can only be found in the relationship between its different measurements. Suitable strategies for visualizing these complicated data have been key to interpretation by physicians and neuroscientists, for drawing conclusions on brain connectivity and for quality control. This article provides an overview of visualization solutions that have been proposed to date, ranging from basic grayscale and color encodings to glyph representations and renderings of fiber tractography. A particular focus is on ongoing and possible future developments in dMRI visualization, including comparative, uncertainty, interactive and dense visualizations.
引用
收藏
页数:15
相关论文
共 50 条
  • [1] A taxonomic guide to diffusion MRI tractography visualization tools
    Laamoumi, Miriam
    Hendriks, Tom
    Chamberland, Maxime
    NMR IN BIOMEDICINE, 2025, 38 (01)
  • [2] Processing and visualization for diffusion tensor MRI
    Westin, CF
    Maier, SE
    Mamata, H
    Nabavi, A
    Jolesz, FA
    Kikinis, R
    MEDICAL IMAGE ANALYSIS, 2002, 6 (02) : 93 - 108
  • [3] White Matter Tract Visualization Using Properties of Termination Coordinate Eigenmaps
    Barrick, Thomas R.
    Lawes, I. Nigel C.
    Clark, Chris A.
    MAGNETIC RESONANCE IN MEDICINE, 2009, 61 (05) : 1261 - 1267
  • [4] Model Averaging and Bootstrap Consensus-based Uncertainty Reduction in Diffusion MRI Tractography
    Gruen, J.
    van der Voort, G.
    Schultz, T.
    COMPUTER GRAPHICS FORUM, 2023, 42 (01) : 217 - 230
  • [5] Visualization of Diffusion Propagator and Multiple Parameter Diffusion Signal
    Vaillancourt, Olivier
    Chamberland, Maxime
    Houde, Jean-Christophe
    Descoteaux, Maxime
    VISUALIZATION AND PROCESSING OF HIGHER ORDER DESCRIPTORS FOR MULTI-VALUED DATA, 2015, : 191 - 212
  • [6] Visualization, Interaction and Tractometry: Dealing with Millions of Streamlines from Diffusion MRI Tractography
    Rheault, Francois
    Houde, Jean-Christophe
    Descoteaux, Maxime
    FRONTIERS IN NEUROINFORMATICS, 2017, 11
  • [7] Disentangling micro from mesostructure by diffusion MRI: A Bayesian approach
    Reisert, Marco
    Kellner, Elias
    Dhital, Bibek
    Hennig, Juergen
    Kiselev, Valerij G.
    NEUROIMAGE, 2017, 147 : 964 - 975
  • [8] On the need for bundle-specific microstructure kernels in diffusion MRI
    Christiaens, Daan
    Veraart, Jelle
    Cordero-Grande, Lucilio
    Price, Anthony N.
    Hutter, Jana
    Hajnal, Joseph V.
    Tournier, J-Donald
    NEUROIMAGE, 2020, 208
  • [9] THEORY AND APPLICATIONS OF DIFFUSION MRI
    Leemans, Alexander
    2010 7TH IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO, 2010, : 628 - 631
  • [10] Mathematical methods for diffusion MRI processing
    Lenglet, C.
    Campbell, J. S. W.
    Descoteaux, M.
    Haro, G.
    Savadjiev, P.
    Wassermann, D.
    Anwander, A.
    Deriche, R.
    Pike, G. B.
    Sapiro, G.
    Siddiqi, K.
    Thompson, P. M.
    NEUROIMAGE, 2009, 45 (01) : S111 - S122