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
  • [21] How and how not to correct for CSF-contamination in diffusion MRI
    Metzler-Baddeley, Claudia
    O'Sullivan, Michael J.
    Bells, Sonya
    Pasternak, Ofer
    Jones, Derek K.
    NEUROIMAGE, 2012, 59 (02) : 1394 - 1403
  • [22] Dimensionality reduction of diffusion MRI measures for improved tractometry of the human brain
    Chamberland, Maxime
    Raven, Erika P.
    Genc, Sila
    Duffy, Kate
    Descoteaux, Maxime
    Parker, Greg D.
    Tax, Chantal M. W.
    Jones, Derek K.
    NEUROIMAGE, 2019, 200 : 89 - 100
  • [23] Diffusion MRI fiber tractography of the brain
    Jeurissen, Ben
    Descoteaux, Maxime
    Mori, Susumu
    Leemans, Alexander
    NMR IN BIOMEDICINE, 2019, 32 (04)
  • [24] Diffusion and functional MRI in surgical neuromodulation
    Silva, Nicole A.
    Barrios-Martinez, Jessica
    Yeh, Fang-Cheng
    Hodaie, Mojgan
    Roque, Daniel
    Boerwinkle, Varina L.
    Krishna, Vibhor
    NEUROTHERAPEUTICS, 2024, 21 (03)
  • [25] Mapping pontocerebellar connectivity with diffusion MRI
    Rousseau, Paul-Noel
    Chakravarty, M. Mallar
    Steele, Christopher J.
    NEUROIMAGE, 2022, 264
  • [26] Ball and rackets: Inferring fiber fanning from diffusion-weighted MRI
    Sotiropoulos, Stamatios N.
    Behrens, Timothy E. J.
    Jbabdi, Saad
    NEUROIMAGE, 2012, 60 (02) : 1412 - 1425
  • [27] Challenges in diffusion MRI tractography - Lessons learned from international benchmark competitions
    Schilling, Kurt G.
    Daducci, Alessandro
    Maier-Hein, Klaus
    Poupon, Cyril
    Houde, Jean-Christophe
    Nath, Vishwesh
    Anderson, Adam W.
    Landman, Bennett A.
    Descoteaux, Maxime
    MAGNETIC RESONANCE IMAGING, 2019, 57 : 194 - 209
  • [28] Recursive calibration of the fiber response function for spherical deconvolution of diffusion MRI data
    Tax, Chantal M. W.
    Jeurissen, Ben
    Vos, Sjoerd B.
    Viergever, Max A.
    Leemans, Alexander
    NEUROIMAGE, 2014, 86 : 67 - 80
  • [29] DiffusionKit: A light one-stop solution for diffusion MRI data analysis
    Xie, Sangma
    Chen, Liangfu
    Zuo, Nianming
    Jiang, Tianzi
    JOURNAL OF NEUROSCIENCE METHODS, 2016, 273 : 107 - 119
  • [30] MRI Diffusion Connectomics-Based Characterization of Progression in Alzheimer's Disease
    Mattie, David
    Pena-Castillo, Lourdes
    Takahashi, Emi
    Levman, Jacob
    APPLIED SCIENCES-BASEL, 2024, 14 (16):