B. Fischl, M.I. Sereno, R.B.H. Tootell, and A.M. Dale. High-resolution inter-subject averaging and a coordinate system for the cortical surface. Human Brain Mapping, 8:272--284, 1999.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....the collection and databasing of brain maps. Nonetheless, computational problems arise when integrating and comparing brain data. One way to analyze and compare brain data is to map them into a canonical space while retaining geometric information on the original structures as far as possible [1, 2, 3, 4, 5, 6]. Fischl et al. 1] demonstrate that surface based brain mapping can o#er advantages over volume based brain mapping, especially when localizing cortical deficits and functional activations. Thompson et al. 4, 5] introduce a mathematical framework based on covariant partial di#erential equations, ....

....of brain maps. Nonetheless, computational problems arise when integrating and comparing brain data. One way to analyze and compare brain data is to map them into a canonical space while retaining geometric information on the original structures as far as possible [1, 2, 3, 4, 5, 6] Fischl et al. [1] demonstrate that surface based brain mapping can o#er advantages over volume based brain mapping, especially when localizing cortical deficits and functional activations. Thompson et al. 4, 5] introduce a mathematical framework based on covariant partial di#erential equations, and pull backs of ....

B. Fischl, M.I. Sereno, R.B.H. Tootell, and A.M. Dale. High-resolution inter-subject averaging and a coordinate system for the cortical surface. In Human Brain Mapping, volume 8, pages 272--284, 1999.

....the collection and databasing of brain maps. Nonetheless, computational problems arise when integrating and comparing brain data. One way to analyze and compare brain data is to map them into a canonical space while retaining geometric information on the original structures as far as possible [1 5]. Fischl et al. 1] demonstrate that surface based brain mapping can o#er advantages over volume based brain mapping, especially when localizing cortical deficits and functional activations. Thompson et al. 4, 5] introduce a mathematical framework based on covariant partial differential ....

....databasing of brain maps. Nonetheless, computational problems arise when integrating and comparing brain data. One way to analyze and compare brain data is to map them into a canonical space while retaining geometric information on the original structures as far as possible [1 5] Fischl et al. [1] demonstrate that surface based brain mapping can o#er advantages over volume based brain mapping, especially when localizing cortical deficits and functional activations. Thompson et al. 4, 5] introduce a mathematical framework based on covariant partial differential equations, and pull backs of ....

B. Fischl, M.I. Sereno, R.B.H. Tootell, and A.M. Dale. High-resolution intersubject averaging and a coordinate system for the cortical surface. In Human Brain Mapping, volume 8, pages 272--284, 1999.

....sulcus. Keywords Sulcogenesis, spatial normalization, morphometry, variability I. INTRODUCTION HE advent of methods dedicated to the automatic analysis of large databases of MRI images of brain anatomy has raised a large interest in the neuroscience community [1] 2] 3] 4] 5] 6] 7] [8], 9] 10] 11] 12] These tools, indeed, provide new ways of addressing issues related to the comparison of brain populations. They allow the study of the influence of various parameters (sex, dominant hemisphere, cognitive features, genetic features, pathology, etc. on the anatomical ....

....However, cortical flattening leads to a significant amount of metric distortion (10 20 in average, locally attaining much higher values [59] 6] and requires the introduction of cuts because of the cortex spherical topology. Using the mapping to a sphere would be an alternative solution [8], but spherical coordinates include two poles leading to some other difficulties. B.2 Local planar parameterization In view of this, the adopted parameterization was a simple local transformation that maps each surface element (a node and its first neighbours) into a plane, while keeping ....

B. Fischl, M. I. Sereno, R. B. Tootle, and A. M. Dale, "High-resolution intersubject averaging and a coordinate system for the cortical surface," Hum Brain Mapp., vol. 8, no. 4, pp. 272--84, 1999.

.... First, the gray white matter interface and the pial surface were extracted from each MRI scan [1, 5] The surfaces were then brought into correspondence by mapping each cortical surface onto a unit sphere while minimizing distortions and then non rigidly aligning the cortical curvature patterns [3, 4]. The cortical thickness was densely sampled at the corresponding locations for all subjects. In this case, the performance of a linear classifier was virtually identical to that of the RBF classifier, and since interpretation of the results is significantly simpler for the linear case, we show ....

B. Fischl, et al. High-resolution intersubject averaging and a coordinate system for the cortical surface. Human Brain Mapping, 8:272-84, 1999.

....create a well resolved, average template of anatomy (Fig. 3(b) and (c) show an average brain template based on N=9 Alzheimer s patients) Here group features are reinforced in their mean anatomic locations ( 16] Fig. 3, panel 6) This method, based on a technique called cortical pattern matching [17 20], can also generate average maps of gyral pattern asymmetry, and gray matter deficits a group, pinpointing disease specific patterns (Fig. 5) Importantly, detailed information is retained on individual variability (Fig. 4(c) d) This is useful for understanding genetic influences on brain ....

Fischl B, Sereno MI, Tootell RBH, Dale AM (1999). High-Resolution Inter-Subject Averaging and a Coordinate System for the Cortical Surface, Hum Brain Mapp. 1999;8(4):272-84.

....it is assumed that analyzing hundreds of brains overcome the failures observed for a few ones. Most of the approaches applied at a large scale rely on a coordinate system, which may be either three dimensional for voxel based morphometry [1] or two dimensional for studies of cortical thickness [8, 14]. In each case, various warping operations are used to match as far as possible the different brains under study with a template endowed with the coordinate system. We will denote this warping principle iconic spatial normalisation . Morphometry is performed on a point by point statistical basis, ....

B. Fischl, M. I. Sereno, R. B. Tootle, and A. M. Dale. High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum Brain Mapp., 8(4):272--84, 1999.

.... non convoluted surface such as a 2D plane (Van Essen and Maunsell, 1980; Carman et al. 1995; Schwartz and Merker, 1986; Drury et al. 1996; Drury and Van Essen, 1997) an ellipsoid (Dale and Sereno, 1993; Sereno et al. 1996) or a sphere (Davatzikos, 1996; Thompson et al. 1996, 1997, 1998, 1999; Fischl et al. 1999). Figure 7 shows examples of these types of maps, with color fields imposed (Thompson and Toga, 1997) to retain 3 dimensional information on cortical geometry. Warping the Cerebral Cortex. Despite the advantages provided by transformations that simplify its geometry, the cortical surface presents ....

....sphere whose corresponding 3D locations are uniformly spaced. A set of 36 average gyral curves for the group is created by vector averaging all point locations on each curve. This average curve template (curves in Fig. 8(b) serves as the target for alignment of individual cortical patterns (cf. Fischl et al. 1999). Each individual cortical pattern is transformed into the average curve configuration using a flow field within the spherical map (Fig. 8(a) b) cf. Bakircioglu et al. 1999) By carrying a color code (that indexes 3D locations) along with the vector flow that aligns each individual with the ....

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Fischl B, Sereno MI, Tootell RBH, Dale AM (1999). High-Resolution Inter-Subject Averaging and a Coordinate System for the Cortical 21 Surface, [in press].

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B. Fischl, M.I. Sereno, R.B.H. Tootell, and A.M. Dale. High-resolution inter-subject averaging and a coordinate system for the cortical surface. Human Brain Mapping, 8:272--284, 1999.

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B. Fischl, M. I. Sereno, R. B. H. Tootell, and A. M. Dale, "High-resolution inter-subject averaging and a coordinate system for the cortical surface," Human Brain Mapping, vol. 8, no. 4, pp. 272--284, 1999.

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B. Fischl et al. High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum Brain Mapp., 8(4):272--84, 1999.

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B. Fischl, M. Sereno, R. Tootell, and A. Dale, "High-resolution intersubject averaging and a coordinate system for the cortical surface," in Human Brain Mapping, vol. 8, 1999, pp. 272--284.

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B. Fischl, M. Sereno, R. Tootell, and A. Dale, "High-resolution intersubject averaging and a coordinate system for the cortical surface," in Human Brain Mapping, vol. 8, 1999, pp. 272--284.

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B. Fischl, M. I. Sereno, R. B. Tootle, and A. M. Dale. High-resolution intersubject averaging and a coordinate system for the cortical surface. Hum Brain Mapp., 8(4):272--84, 1999.

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Fischl B, Sereno MI, Tootell RBH, Dale AM. Highresolution inter-subject averaging and a coordinate system for the cortical surface. Hum Brain Mapp

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Fischl, B., Sereno, M.I., Tootell, R.B.H., Dale, A.M.: High-Resolution Inter-Subject Averaging and a Coordinate System for the Cortical Surface. Hum. Brain Mapp. 8(4), 272--284 (1999)

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Fischl B, Sereno MI, Tootell RBH, Dale AM. High-Resolution Inter-Subject Averaging and a Coordinate System for the Cortical Surface, Hum Brain Mapp. 1999;8(4):272-84.

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