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Spherical U-Net on Cortical Surfaces: Methods and Applications
[article]
2019
arXiv
pre-print
Convolutional Neural Networks (CNNs) have been providing the state-of-the-art performance for learning-related problems involving 2D/3D images in Euclidean space. However, unlike in the Euclidean space, the shapes of many structures in medical imaging have a spherical topology in a manifold space, e.g., brain cortical or subcortical surfaces represented by triangular meshes, with large inter-subject and intrasubject variations in vertex number and local connectivity. Hence, there is no
arXiv:1904.00906v1
fatcat:dwa2j6kwang6te4igp6tjk2mcq