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Multi-atlas labeling with population-specific template and non-local patch-based label fusion

We propose a new method combining a population-specific nonlinear template atlas approach with non-local patch-based structure segmentation for whole brain segmentation into individual structures. This way, we benefit from the efficient intensity-driven segmentation of the non-local means framework and from the global shape constraints imposed by the nonlinear template matching.