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Segmentation and representation of the human cerebral cortex from magnetic resonance (MR) images play an important role in neuroscience and medicine. A successful segmentation method must be robust to various imaging artifacts and produce anatomically meaningful and consistent cortical representations. A method for the automatic reconstruction of the inner,(More)
The human cortical surface is a highly complex, folded structure. Sulci, the spaces between the folds, define location on the cortex and provide a parcellation into anatomically distinct areas. A topic that has recently received increased attention is the segmentation of these sulci from magnetic resonance images, with most work focusing on extracting(More)
Visualization and mapping of function on the cortical surface is difficult because of its sulcal and gyral convolutions. Methods to unfold and flatten the cortical surface for visualization and measurement have been described in the literature. This makes visualization and measurement possible, but comparison across multiple subjects is still difficult(More)
Imaging studies of the human brain indicate that the cortex undergoes anatomic changes during the aging process. With the ability to study the human brain in vivo using magnetic resonance imaging, understanding the nature and location of these changes is of increasing interest. In this work, we investigate cross-sectional and longitudinal age effects on the(More)
Reconstructing the geometry of the human cerebral cortex from MR images is an important step in both brain mapping and surgical path planning applications. Difficulties with imaging noise, partial volume averaging, image intensity inhomogeneities, convoluted cortical structures, and the requirement to preserve anatomical topology make the development of(More)
Segmentation and mapping of the human cerebral cortex from magnetic resonance (MR) images plays an important role in neuroscience and medicine. This paper describes a comprehensive approach for cortical reconstruction, flattening, and sulcal segmentation. Robustness to imaging artifacts and anatomical consistency are key achievements in an overall approach(More)
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 marching method. They are then transformed to curves on the unit sphere via a conformal(More)
Two different studies were conducted to assess the accuracy and precision of an algorithm developed for automatic reconstruction of the cerebral cortex from T1-weighted magnetic resonance (MR) brain images. Repeated scans of three different brains were used to quantify the precision of the algorithm, and manually selected landmarks on different sulcal(More)
With the improvements in techniques for generating surface models from magnetic resonance (MR) images, it has recently become feasible to study the morphological characteristics of the human brain cortex in vivo. Studies of the entire surface are important for measuring global features, but analysis of specific cortical regions of interest provides a more(More)