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Automatic segmentation of neonatal images using convex optimization and coupled level sets
2011
Accurate segmentation of neonatal brain MR images remains challenging mainly due to their poor spatial resolution, inverted contrast between white matter and gray matter, and high intensity inhomogeneity. Most existing methods for neonatal brain segmentation are atlas-based and voxel-wise. Although active contour/surface models with geometric information constraint have been successfully applied to adult brain segmentation, they are not fully explored in the neonatal image segmentation. In this
doi:10.17615/p1fq-jv46
fatcat:7lopiqwaejdh5edxnbvusfok5e