Cortical surface segmentation and mapping

Duygu Tosun; Maryam E. Rettmann; Xiao Han; Xiaodong Tao; Chenyang Xu; Susan M. Resnick; Dzung L. Pham; Jerry L. Prince

doi:10.1016/j.neuroimage.2004.07.042

Cortical surface segmentation and mapping

Duygu Tosun, Maryam E. Rettmann, Xiao Han, Xiaodong Tao, Chenyang Xu, Susan M. Resnick, Dzung L. Pham, Jerry L. Prince

Whiting School of Engineering

Research output: Contribution to journal › Article › peer-review

50 Scopus citations

Abstract

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 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.

Original language	English (US)
Pages (from-to)	S108-S118
Journal	NeuroImage
Volume	23
Issue number	SUPPL. 1
DOIs	https://doi.org/10.1016/j.neuroimage.2004.07.042
State	Published - 2004

Keywords

Cerebral cortex
Cortical surface
Cortical thickness
Surface flattening

ASJC Scopus subject areas

Neurology
Cognitive Neuroscience

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10.1016/j.neuroimage.2004.07.042

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title = "Cortical surface segmentation and mapping",

abstract = "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 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.",

keywords = "Cerebral cortex, Cortical surface, Cortical thickness, Surface flattening",

author = "Duygu Tosun and Rettmann, {Maryam E.} and Xiao Han and Xiaodong Tao and Chenyang Xu and Resnick, {Susan M.} and Pham, {Dzung L.} and Prince, {Jerry L.}",

note = "Funding Information: The authors would like to thank Dr. Noor Kabani for providing the hand-labeled atlas data and Kirsten Behnke for assistance with the atlas data. This work was supported in part by NIH/NINDS Grant R01NS37747.",

year = "2004",

doi = "10.1016/j.neuroimage.2004.07.042",

language = "English (US)",

volume = "23",

pages = "S108--S118",

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T1 - Cortical surface segmentation and mapping

AU - Tosun, Duygu

AU - Rettmann, Maryam E.

AU - Han, Xiao

AU - Tao, Xiaodong

AU - Xu, Chenyang

AU - Resnick, Susan M.

AU - Pham, Dzung L.

AU - Prince, Jerry L.

N1 - Funding Information: The authors would like to thank Dr. Noor Kabani for providing the hand-labeled atlas data and Kirsten Behnke for assistance with the atlas data. This work was supported in part by NIH/NINDS Grant R01NS37747.

PY - 2004

Y1 - 2004

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AB - 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 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.

KW - Cerebral cortex

KW - Cortical surface

KW - Cortical thickness

KW - Surface flattening

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Cortical surface segmentation and mapping

Abstract

Keywords

ASJC Scopus subject areas

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