3 research outputs found

    Statistical Study on Cortical Sulci of Human Brains

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    Abstract. A method for building a statistical shape model of sulci of the human brain cortex is described. The model includes sulcal fundi that are defined on a spherical map of the cortex. The sulcal fundi are first extracted in a semi-automatic way using an extension of the fast march-ing method. They are then transformed to curves on the unit sphere via a conformal mapping method that maps each cortical point to a point on the unit sphere. The curves that represent sulcal fundi are parameterized with piecewise constant-speed parameterizations. Intermediate points on these curves correspond to sulcal landmarks, which are used to build a point distribution model on the unit sphere. Statistical information of local properties of the sulci, such as curvature and depth, are embedded in the model. Experimental results are presented to show how the models are built.

    A New Approach to 3D Sulcal Ribbon Finding from MR Images

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    . Sulcal medial surfaces are 3D thin convoluted ribbons embedded in cortical sulci, and they provide distinctive anatomical features of the brain. Here we propose a new approach to automatic intrasulcal ribbon finding, following our work on cortex segmentation with coupled surfaces via level set methods, where the outer cortical surface is embedded as the zero level set of a high-dimensional distance function. Through the utilization of this distance function, we are able to formulate the sulcal ribbon finding problem as one of surface deformation, thus avoiding possible control problems in other work using sliding contour models. Using dynamic programming and deformable surface models, our method requires little manual intervention and results parameterized sulcal ribbon surfaces in nearly real-time. Though a natural follow up to our earlier segmentation work, we describe how it can be applied with general segmentation methods. We also present quantitative results on 15 MR brain image..

    A model-based cortical parcellation scheme for high-resolution 7 Tesla MRI data

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