DTI registration in atlas based fiber analysis of infantile Krabbe disease.
In recent years, diffusion tensor imaging (DTI) has become the modality of choice to investigate white matter pathology in the developing brain. To study neonate Krabbe disease with DTI, we evaluate the performance of linear and non-linear DTI registration algorithms for atlas based fiber tract analysis. The DTI scans of 10 age-matched neonates with infantile Krabbe disease are mapped into an atlas for the analysis of major fiber tracts - the genu and splenium of the corpus callosum, the internal capsules tracts and the uncinate fasciculi. The neonate atlas is based on 377 healthy control subjects, generated using an unbiased diffeomorphic atlas building method. To evaluate the performance of one linear and seven nonlinear commonly used registration algorithms for DTI we propose the use of two novel evaluation metrics: a regional matching quality criterion incorporating the local tensor orientation similarity, and a fiber property profile based metric using normative correlation. Our experimental results indicate that the whole tensor based registration method within the DTI-ToolKit (DTI-TK) shows the best performance for our application.
School of Electronics and Information, Northwestern Polytechnical University, Xi'an, Shaanxi, China.
Yi
Y
Wang
Aditya
A
Gupta
Zhexing
Z
Liu
Hui
H
Zhang
Maria L
ML
Escolar
John H
JH
Gilmore
Sylvain
S
Gouttard
Pierre
P
Fillard
Eric
E
Maltbie
Guido
G
Gerig
Martin
M
Styner
D000465:Algorithms; D003198:Computer Simulation; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007223:Infant; D007231:Infant, Newborn; D007965:Leukodystrophy, Globoid Cell / Q000473:pathology*; D008297:Male; D008953:Models, Anatomic; D009413:Nerve Fibers, Myelinated / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique
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