Cortical surface segmentation and mapping

Abstract

Segmentation and mapping of the human cerebral cortex from magnetic resonance (MR) images plays an important role in neuro-science 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 that is nearly fully automatic and computationally fast. Results demonstrating the application of this approach to a study of cortical thickness changes in aging are presented.

Generalized <i>α</i>-Entropy Based Medical Image Segmentation

“…By applying the closing morphological operation, we can get rid of the holes form the binary image. Furthermore Opening operation with small structure element can be used to separate some objects that are still connected in small number of pixels [25,26].…”

Quantification of Volumetric Changes of Brain in Neurodegenerative Diseases Using Magnetic Resonance Imaging and Stereology

“…Images of brain are cleared brain contour using morphological image processing. This method involves two major steps and final segmented images result from separation of parenchyma for brain volume and surrounding line for cortical surface area of the brain (Tosun et al, 2004;Ueda et al, 2009;Brouwer et al, 2010;Lui et al, 2010) (Fig. 4).…”

Brain Functional Localization: A Survey of Image Registration Techniques

“…A few of the surface reconstruction algorithms have been implemented as software tools for surface visualization and mapping. The tools listed in Table II are Surefit, based on the technique of Van Essen et al [288], Freesurfer by Fischl et al [281], [292], [293], BrainSuite by Shattuck and Leahy [294], and Cortical reconstruction using implicit surface evolution (CRUISE) by the Image Analysis and Communications group at Johns Hopkins University (Baltimore, MD) [283], [295]. Most of these techniques are based on initial segmentations for white matter, gray matter, and cerbrosplinal fluid tissue classification, triangular tessellation for reconstruction, and a topology correction method to provide geometrical smoothness and topology preservation [296].…”

“…The required steps to go from the cortical surface reconstruction to the surface registration and visualization for functional localization include cortical surface inflation, flattening and probably more advanced structural segmentation [292], [295], [301]. Inflation is useful for visualization, and flattening to planar, spherical or ellipsoidal maps is a simplification to permit registration of the cortical surface to surface-based standard coordinates [288], [302]- [304].…”