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A Supervised Framework for the Registration and Segmentation of White Matter Fiber Tracts

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5 Author(s)
Arnaldo Mayer ; Biomedical Engineering Dept., Medical image processing Lab., Tel-Aviv, Israel ; Gali Zimmerman-Moreno ; Ran Shadmi ; Amit Batikoff
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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.

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IEEE Transactions on Medical Imaging  (Volume:30 ,  Issue: 1 )