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Cortical surface-based analysis. I. Segmentation and surface reconstruction

by Anders M. Dale, Bruce Fischl, Martin I. Sereno - Neuroimage , 1999
"... Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical pr ..."
Abstract - Cited by 450 (42 self) - Add to MetaCart
Several properties of the cerebral cortex, including its columnar and laminar organization, as well as the topographic organization of cortical areas, can only be properly understood in the context of the intrinsic two-dimensional structure of the cortical surface. In order to study such cortical properties in humans, it is necessary to obtain an accurate and explicit representation of the cortical surface in individual subjects. Here we describe a set of automated procedures for obtaining accurate reconstructions of the cortical surface, which have been applied to data from more than 100 subjects, requiring little or no manual intervention. Automated routines for unfolding and flattening the cortical surface are described in a companion paper. These procedures allow for the routine use of cortical surface-based analysis and visualization methods in functional brain imaging.

Mapping the structural core of human cerebral cortex

by Patric Hagmann, Leila Cammoun, Xavier Gig, Reto Meuli, Christopher J. Honey, Van J. Wedeen - PLoS Biol
"... Structurally segregated and functionally specialized regions of the human cerebral cortex are interconnected by a dense network of cortico-cortical axonal pathways. By using diffusion spectrum imaging, we noninvasively mapped these pathways within and across cortical hemispheres in individual human ..."
Abstract - Cited by 221 (4 self) - Add to MetaCart
Structurally segregated and functionally specialized regions of the human cerebral cortex are interconnected by a dense network of cortico-cortical axonal pathways. By using diffusion spectrum imaging, we noninvasively mapped these pathways within and across cortical hemispheres in individual human participants. An analysis of the resulting large-scale structural brain networks reveals a structural core within posterior medial and parietal cerebral cortex, as well as several distinct temporal and frontal modules. Brain regions within the structural core share high degree, strength, and betweenness centrality, and they constitute connector hubs that link all major structural modules. The structural core contains brain regions that form the posterior components of the human default network. Looking both within and outside of core regions, we observed a substantial correspondence between structural connectivity and resting-state functional connectivity measured in the same participants. The spatial and topological centrality of the core within cortex suggests an important role in functional integration.
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Automatically parcellating the human cerebral cortex.

by Bruce Fischl , André Van Der Kouwe , Christophe Destrieux , Eric Halgren , Florent Ségonne , David H Salat , Evelina Busa , Larry J Seidman , Jill Goldstein , David Kennedy , Verne Caviness , Nikos Makris , Bruce Rosen , Anders M Dale , Bruce Fischl - Cereb. Cortex , 2004
"... Abstract -We present a technique for automatically assigning a neuroanatomical label to each location on a cortical surface model based on probabilistic information estimated from Introduction Techniques for labeling geometric features of the cerebral cortex are useful for analyzing a variety of fu ..."
Abstract - Cited by 189 (14 self) - Add to MetaCart
Abstract -We present a technique for automatically assigning a neuroanatomical label to each location on a cortical surface model based on probabilistic information estimated from Introduction Techniques for labeling geometric features of the cerebral cortex are useful for analyzing a variety of functional and structural neuroimaging data Unfortunately, despite their potential utility, cortical parcellations are not commonly used in the neuroimaging community due to the difficult and time-consuming nature of the task of manually parcellating the entire cortex from high-resolution MRI images. While many techniques exist for labeling parts of the cortex The inclusion of prior information is a critical feature of a cortical parcellation algorithm. The reason this is the case is that the divisions that are useful in a cortical parcellation scheme can be based on properties of the brain other than cortical geometry. Many disparate pieces of information, such as knowledge of structure-function relationship, and cytoarchitectonic or receptor labeling properties of regions, may be used by a neuroanatomist in generating a cortical parcellation -information that is not directly available to an automated parcellation procedure from magnetic resonance imaging (MRI) data. A trivial example of this is the fact that many unbroken sulci change names as lobar boundaries are crossed. In addition, functional heterogeneity can make it desirable for adjacent areas to be assigned different labels despite the absence of macroscopic cortical features to distinguish them. Conversely, there are situations in which the secondary folding structure of the cortex (i.e. folds within folds) carries information, such as the location of the hand area in primary motor cortex, which is well predicted by a posterior-pointing secondary fold in the precentral gyrus Various approaches have been taken to the problem of labeling of cortical features. For example, Sandor and Leahy (Sandor and Leahy, 1997) use a manually labeled atlas brain, which is then warped into correspondence with an individual subject's surface model. The individual subject surface then inherits the labels from the atlas. Similar surface-fitting approaches have been developed by Here we present a technique for using manually labeled data as the basis for an automated parcellation procedure, using an intrinsically cortical coordinate system to store prior statistics and classconditional densities . The use of the manual parcellation as a training set allows the technique to incorporate neuroanatomical convention into the parcellation in regions in which geometry alone is not predictive of a parcellation label. The procedure models the parcellation labels as a first order anisotropic nonstationary Markov random field (MRF), allowing it to capture the spatial relationships between parcellation units that are present in the training set. The anisotropy separates label probabilities in the first and second principal curvature directions, in order to encode the increased probability of differing labels in the direction of maximal curvature. This type of modeling allows the procedure to automatically encode information such as "precentral gyrus frequently neighbors central sulcus in the direction of high curvature (moving across the sulcus), but not in the direction of low curvature (along the banks of the sulcus)". This type of parcellation has commonly been generated by a having a trained anatomist or technician manually label some or all of the structures in the cortex, a procedure that can take up to a week for high-resolution images. Here, we use the results of the manual labeling using the validated techniques of the Center for Morphometric Analysis (CMA)
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Automated Manifold Surgery: Constructing Geometrically Accurate and Topologically Correct Models of the Human Cerebral Cortex

by Bruce Fischl, Arthur Liu, Anders M. Dale , 2001
"... Highly accurate surface models of the cerebral cortex are becoming increasingly important as tools in the investigation of the functional organization of the human brain. The construction of such models is difficult using current neuroimaging technology due to the high degree of cortical folding. E ..."
Abstract - Cited by 167 (25 self) - Add to MetaCart
Highly accurate surface models of the cerebral cortex are becoming increasingly important as tools in the investigation of the functional organization of the human brain. The construction of such models is difficult using current neuroimaging technology due to the high degree of cortical folding. Even single voxel misclassifications can result in erroneous connections being created between adjacent banks of a sulcus, resulting in a topologically inaccurate model. These topological defects cause the cortical model to no longer be homeomorphic to a sheet, preventing the accurate inflation, flattening, or spherical morphing of the reconstructed cortex. Surface deformation techniques can guarantee the topological correctness of a model, but are time-consuming and may result in geometrically inaccurate models. In order to address this need we have developed a technique for taking a model of the cortex, detecting and fixing the topological defects while leaving that majority of the model intact, resulting in a surface that is both geometrically accurate and topologically correct.
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A hybrid approach to the skull stripping problem in MRI

by F. Ségonne, A. M. Dale, B E. Busa, B M. Glessner, B D. Salat, B H. K. Hahn, B. Fischl A - NeuroImage , 2004
"... We present a novel skull-stripping algorithm based on a hybrid approach that combines watershed algorithms and deformable surface models. Our method takes advantage of the robustness of the former as well as the surface information available to the latter. The algorithm first localizes a single whit ..."
Abstract - Cited by 127 (11 self) - Add to MetaCart
We present a novel skull-stripping algorithm based on a hybrid approach that combines watershed algorithms and deformable surface models. Our method takes advantage of the robustness of the former as well as the surface information available to the latter. The algorithm first localizes a single white matter voxel in a T1-weighted MRI image, and uses it to create a global minimum in the white matter before applying a watershed algorithm with a preflooding height. The watershed algorithm builds an initial estimate of the brain volume based on the three-dimensional connectivity of the white matter. This first step is robust, and performs well in the presence of intensity nonuniformities and noise, but may erode parts of the cortex that abut bright nonbrain structures such as the eye sockets, or may remove parts of the cerebellum. To correct these inaccuracies, a surface deformation process fits a smooth surface to the masked volume, allowing the incorporation of geometric constraints into the skullstripping procedure. A statistical atlas, generated from a set of accurately segmented brains, is used to validate and potentially correct the segmentation, and the MRI intensity values are locally re-estimated at the boundary of the brain. Finally, a high-resolution surface deformation is performed that accurately matches the outer boundary of the brain, resulting in a robust and automated procedure. Studies by our group and others outperform other publicly available skullstripping tools.
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Sequence-independent segmentation of magnetic resonance images

by Bruce Fischl, David H. Salat, A Nikos Makris, Florent Ségonne, B Brian T. Quinn, Anders M. Dale A - Neuroimage , 2004
"... We present a set of techniques for embedding the physics of the imaging process that generates a class of magnetic resonance images (MRIs) into a segmentation or registration algorithm. This results in substantial invariance to acquisition parameters, as the effect of these parameters on the contras ..."
Abstract - Cited by 112 (20 self) - Add to MetaCart
We present a set of techniques for embedding the physics of the imaging process that generates a class of magnetic resonance images (MRIs) into a segmentation or registration algorithm. This results in substantial invariance to acquisition parameters, as the effect of these parameters on the contrast properties of various brain structures is explicitly modeled in the segmentation. In addition, the integration of image acquisition with tissue classification allows the derivation of sequences that are optimal for segmentation purposes. Another benefit of these procedures is the generation of probabilistic models of the intrinsic tissue parameters that cause MR contrast (e.g., T1, proton density, T2*), allowing access to these physiologically relevant parameters that may change with disease or demographic, resulting in nonmorphometric alterations in MR images that are otherwise difficult to detect. Finally, we also present a high band width multiecho FLASH pulse sequence that results in high signal-to-noise ratio with minimal image distortion due to B0 effects. This sequence has the added benefit of allowing the explicit estimation of T2 * and of reducing test–retest intensity variability.
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Image distortion correction in fMRI: a quantitative evaluation

by Chloe Hutton, Andreas Bork, Oliver Josephs, Ralf Deichmann, John Ashburner, Robert Turner - NeuroImage , 2002
"... A well-recognized problem with the echo-planar imaging (EPI) technique most commonly used for functional magnetic resonance imaging (fMRI) studies is geometric distortion caused by magnetic field inhomogeneity. This makes it difficult to achieve an accurate registration between a functional activati ..."
Abstract - Cited by 96 (10 self) - Add to MetaCart
A well-recognized problem with the echo-planar imaging (EPI) technique most commonly used for functional magnetic resonance imaging (fMRI) studies is geometric distortion caused by magnetic field inhomogeneity. This makes it difficult to achieve an accurate registration between a functional activation map calculated from an EPI time series and an undistorted, high resolution anatomical image. A correction method based on mapping the spatial distribution of field inhomogeneities can be used to reduce these distortions. This approach is attractive in its simplicity but requires postprocessing to improve the robustness of the acquired field map and reduce any secondary artifacts. Furthermore, the distribution of the internal magnetic field throughout the head is position dependent resulting in an interaction between distortion and head motion. Therefore, a single field map may not be sufficient to correct for the distortions throughout a whole fMRI time series. In this paper we present a quantitative evaluation of image distortion correction for fMRI at 2T. We assess (i) methods for the acquisition and calculation of field maps, (ii) the effect of image distortion correction on the coregistration between anatomical and functional images, and (iii) the interaction between distortion and head motion, assessing the feasibility of using field maps to reduce this effect. We propose that field maps with acceptable noise levels can be generated easily using a dual echo-time EPI sequence and demonstrate the importance of distortion correction for anatomical coregistration, even for small distortions. Using a dual echo-time series to generate a unique field map at each time point, we characterize the interaction between head motion and geometric distortion. However, we suggest that the variance between successively measured field maps introduces additional unwanted variance in the voxel time-series and is therefore not adequate to correct for time-varying distortions. © 2002 Elsevier Science (USA)
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Detecting changes in nonisotropic images

by K. J. Worsley, M. Andermann, T. Koulis, D. Macdonald, A. C. Evans - Human Brain Mapping , 1999
"... Abstract: If the noise component of image data is non-isotropic, that is, if it has nonconstant smoothness or effective point spread function in every direction, then theoretical results for the P-value of local maxima and the size of supra-threshold clusters of a statistical parametric map (SPM) ba ..."
Abstract - Cited by 72 (13 self) - Add to MetaCart
Abstract: If the noise component of image data is non-isotropic, that is, if it has nonconstant smoothness or effective point spread function in every direction, then theoretical results for the P-value of local maxima and the size of supra-threshold clusters of a statistical parametric map (SPM) based on random field theory are not valid. This assumption is reasonable for PET or smoothed fMRI data, but not if this data is projected onto an unfolded, inflated or flattened 2D cortical surface. Anatomical data such as structure masks, surface displacements and deformation vectors are also highly non-isotropic. The solution proposed in this paper is to suppose that the image can be warped or flattened (in a statistical sense) into a space where the data is isotropic. The subsequent corrected P-values do not depend on finding this warping – it is only sufficient to know that such a warping exists. Key words: SPM, random fields.
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fMRI responses to video and point light displays of moving humans and manipulatable objects

by Michael S. Beauchamp, Kathryn E. Lee, James V. Haxby, Alex Martin - J. Cogn. Neurosci
"... & We used fMRI to study the organization of brain responses to different types of complex visual motion. In a rapid event-related design, subjects viewed video clips of humans perform-ing different whole-body motions, video clips of manmade manipulable objects (tools) moving with their character ..."
Abstract - Cited by 69 (7 self) - Add to MetaCart
& We used fMRI to study the organization of brain responses to different types of complex visual motion. In a rapid event-related design, subjects viewed video clips of humans perform-ing different whole-body motions, video clips of manmade manipulable objects (tools) moving with their characteristic natural motion, point-light displays of human whole-body motion, and point-light displays of manipulable objects. The lateral temporal cortex showed strong responses to both moving videos and moving point-light displays, support-ing the hypothesis that the lateral temporal cortex is the cortical locus for processing complex visual motion. Within the lateral temporal cortex, we observed segregated responses to different types of motion. The superior temporal sulcus (STS) responded strongly to human videos and human point-light displays, while the middle temporal gyrus (MTG) and the inferior temporal sulcus responded strongly to tool videos and tool point-light displays. In the ventral temporal cortex, the lateral fusiform responded more to human videos than to any other stimulus category while the medial fusiform preferred tool videos. The relatively weak responses observed to point-light displays in the ventral temporal cortex suggests that form, color, and texture (present in video but not point-light displays) are the main contributors to ventral temporal activity. In contrast, in the lateral temporal cortex, the MTG responded as strongly to point-light displays as to videos, suggesting that motion is the key determinant of response in the MTG. Whereas the STS responded strongly to point-light displays, it showed an even larger response to video displays, suggesting that the STS integrates form, color, and motion information. &
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Topology correction in brain cortex segmentation using a multiscale, graph-based algorithm

by Xiao Han, Chenyang Xu, Ulisses Braga-neto, Jerry L. Prince, Senior Member - IEEE Trans. Med. Imaging , 2002
"... Abstract — Reconstructing an accurate and topologically correct representation of the cortical surface of the brain is an important objective in various neuroscience applications. Most cortical surface reconstruction methods either ignore topology or correct it using manual editing or methods that l ..."
Abstract - Cited by 66 (7 self) - Add to MetaCart
Abstract — Reconstructing an accurate and topologically correct representation of the cortical surface of the brain is an important objective in various neuroscience applications. Most cortical surface reconstruction methods either ignore topology or correct it using manual editing or methods that lead to inaccurate reconstructions. Shattuck and Leahy recently reported a fully-automatic method that yields a topologically correct representation with little distortion of the underlying segmentation. We provide an alternate approach that has several advantages over their approach, including the use of arbitrary digital connectivities, a flexible morphology-based multiscale approach, and the option of foreground-only or background-only correction. A detailed analysis of the method's performance on 15 magnetic resonance brain images is provided.
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