Analysis of new diffusion tensor imaging anisotropy measures in the three-phase plot.
OBJECTIVE
To evaluate diffusion anisotropy from diffusion tensor imaging using new measures derived from Hellinger divergences and from compositional data distances.


METHODS
New anisotropy measures obtained from the diffusion tensor imaging were measured and compared with classic ones such as fractional anisotropy (FA) and relative anisotropy (RA). The evaluation was done using the three-phase plot (3P-plot). The measures were compared with regard to their sensitivity to detect white and gray matter changes on human DTI data acquired from five normal volunteers. For each volunteer, different volumes of interest located in white matter (WM) and gray matter (GM) were considered.


RESULTS
The proposed Compositional Kullback-Leibler (KLA) and the classic FA had a similar behavior, although KLA detected better the transitions between white and gray matter. Moreover, KLA showed a better discrimination in areas with great confluence of fibers.


CONCLUSIONS
KLA detects better than FA the difference between WM and GM. This leads KLA to be a good measure for segmenting WM from GM.
Graphics and Imaging Laboratory, University of Girona, 17071 Girona, Spain.
Ferran
F
Prados
Imma
I
Boada
Alberto
A
Prats-Galino
Josep Antoni
JA
Martín-Fernández
Miquel
M
Feixas
Gerard
G
Blasco
Josep
J
Puig
Salvador
S
Pedraza
D000465:Algorithms; D016880:Anisotropy; D001921:Brain / Q000033:anatomy & histology / Q000473:pathology*; D001931:Brain Mapping; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D015233:Models, Statistical; D011336:Probability