Average brain models: a convergence study
Computer Vision and Image Understanding - Special issue on analysis of volumetric image
Linear combination of transformations
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
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Probabilistic atlases have been established in the literature as a standard tool for enhancing the intensity-based classification of brain MRl. The rapidly growing neonatal brain requires an age-specific spatial probabilistic atlas to guide the segmentation process. In this paper we describe a method for dynamically creating a probabilistic atlas for any chosen stage of neonatal brain development. The atlas is created from the segmentations of 153 subjects of different ages using a kernel regression method. For any given age, an intensity template as well as the corresponding tissue probability maps with the correct sizes and shapes of the structures can be dynamically generated. The resulting atlas provides prior tissue probability maps for six structures - cortex, white matter, subcortical gray matter, brainstem and cerebellum, for ages of 29 to 44 weeks of gestation.