2004
DOI: 10.1016/j.neuroimage.2004.06.043
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CRUISE: Cortical reconstruction using implicit surface evolution

Abstract: 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, central, and outer surfaces of the cerebral cortex from T1-weighted MR brain images is presented. The method combines a fuzzy tissue classification method,… Show more

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Cited by 237 publications
(271 citation statements)
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“…If needed, the tissue density images were further manually corrected for inaccurate skull-stripping and tissue probabilities were re-calculated. Based on the tissue density images, each individual’s cortical surface was extracted using a cortical reconstruction method using an implicit surface evolution (CRUISE) technique (33), which was shown to yield an accurate and topologically correct representation that lies at the geometric center of the cortical GM tissue (34). Each resulting cortical surface was represented as a triangle mesh comprising of approximately 300,000 mesh nodes.…”
Section: Methodsmentioning
confidence: 99%
“…If needed, the tissue density images were further manually corrected for inaccurate skull-stripping and tissue probabilities were re-calculated. Based on the tissue density images, each individual’s cortical surface was extracted using a cortical reconstruction method using an implicit surface evolution (CRUISE) technique (33), which was shown to yield an accurate and topologically correct representation that lies at the geometric center of the cortical GM tissue (34). Each resulting cortical surface was represented as a triangle mesh comprising of approximately 300,000 mesh nodes.…”
Section: Methodsmentioning
confidence: 99%
“…Surface based methods typically construct a triangulated mesh based on either the WM boundary Fischl et al, 1999;Fischl and Dale, 2000;Shattuck and Leahy, 2002;Xu et al, 1999;Han et al, 2004), or the pial boundary (Davatzikos and Bryan, 1996), which is then deformed to find the opposing boundary.…”
Section: Introductionmentioning
confidence: 99%
“…Surface based cortical thickness methods try to ensure correct topology of the surface after initial segmentation of the WM boundary (Shattuck and Leahy, 2001;Xu et al, 1999;Han et al, 2004), using smoothness and self intersection constraints MacDonald et al, 2000), by correcting topological defects as they occur (Fischl et al, 2001;Segonne et al, 2005), or using a Laplacian function (Kim et al, 2005). Ensuring correct topology or surface regularity massively increases computational cost (Fischl et al, 2001;Han et al, 2004), may require a difficult balance of parameter weights (Kim et al, 2005;Scott et al, 2009), and reduces the model's ability to follow areas of high curvature such as extremely thin gyral stalks (Lohmann et al, 2003) or opposing sides of sulci with no clear CSF between, which can produce bias and error in thickness measurements (Scott et al, 2009).…”
Section: Introductionmentioning
confidence: 99%
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“…A battery of algorithms has been integrated in the proposed framework. These algorithms have been described and validated in detail in various publications [5,6,7,8]. We specifically aimed to test the hypothesis that there exists group differences in cortical atrophy patterns among PSP, MSA, and IPD.…”
Section: Introductionmentioning
confidence: 99%