Abstract
A supervised framework is presented for the automatic registration and segmentation of white matter (WM) tractographies extracted from brain DT-MRI. The framework relies on the direct registration between the fibers, without requiring any intensity-based registration as preprocessing. An affine transform is recovered together with a set of segmented fibers. A recently introduced probabilistic boosting tree classifier is used in a segmentation refinement step to improve the precision of the target tract segmentation. The proposed method compares favorably with a state-of-the-art intensity-based algorithm for affine registration of DTI tractographies. Segmentation results for 12 major WM tracts are demonstrated. Quantitative results are also provided for the segmentation of a particularly difficult case, the optic radiation tract. An average precision of 80% and recall of 55% were obtained for the optimal configuration of the presented method.
Original language | English |
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Article number | 5549914 |
Pages (from-to) | 131-145 |
Number of pages | 15 |
Journal | IEEE Transactions on Medical Imaging |
Volume | 30 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2011 |
Keywords
- Brain
- registration
- segmentation
- tractography
- white matter fiber tracts