Atlas-based fiber reconstruction from diffusion tensor MRI data.
OBJECTIVE
Develop a neural fiber reconstruction method based on diffusion tensor imaging, which is not as sensitive to user-defined regions of interest as streamline tractography.


METHODS
A simulated annealing approach is employed to find a non-rigid transformation to map a fiber bundle from a fiber atlas to another fiber bundle, which minimizes a specific energy functional. The energy functional describes how well the transformed fiber bundle fits the patient's diffusion tensor data.


RESULTS
The feasibility of the method is demonstrated on a diffusion tensor software phantom. We analyze the behavior of the algorithm with respect to image noise and number of iterations. First results on the datasets of patients are presented.


CONCLUSIONS
The described method maps fiber bundles based on diffusion tensor data and shows high robustness to image noise. Future developments of the method should help simplify inter-subject comparisons of fiber bundles.
Fraunhofer MEVIS, Institute for Medical Image Computing, Universitätsallee 29, 28359, Bremen, Germany. sebastiano.barbieri@mevis.fraunhofer.de
Sebastiano
S
Barbieri
Jan
J
Klein
Miriam H A
MH
Bauer
Christopher
C
Nimsky
Horst K
HK
Hahn
D000465:Algorithms; D001271:Atlases as Topic; D001931:Brain Mapping / Q000379:methods*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005240:Feasibility Studies; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D009434:Neural Pathways / Q000033:anatomy & histology*; D019047:Phantoms, Imaging; D012984:Software