Least-square conformal brain mapping with spring energy

Jingxin Nie; Tianming Liu; Gang Li; Geoffrey Young; Ashley Tarokh; Lei Guo; Stephen T.C. Wong

doi:10.1016/j.compmedimag.2007.08.009

Least-square conformal brain mapping with spring energy

Jingxin Nie, Tianming Liu, Gang Li, Geoffrey Young, Ashley Tarokh, Lei Guo, Stephen T.C. Wong

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

6 Scopus citations

Abstract

The human brain cortex is a highly convoluted sheet. Mapping of the cortical surface into a canonical coordinate space is an important tool for the study of the structure and function of the brain. Here, we present a technique based on least-square conformal mapping with spring energy for the mapping of the cortical surface. This method aims to reduce the metric and area distortion while maintaining the conformal map and computation efficiency. We demonstrate through numerical results that this method effectively controls metric and area distortion, and is computational efficient. This technique is particularly useful for fast visualization of the brain cortex.

Original language	English (US)
Pages (from-to)	656-664
Number of pages	9
Journal	Computerized Medical Imaging and Graphics
Volume	31
Issue number	8
DOIs	https://doi.org/10.1016/j.compmedimag.2007.08.009
State	Published - Dec 2007

Keywords

Angle distortion
Area distortion
Brain cortex
Brain mapping
Conformal mapping
Spring energy

ASJC Scopus subject areas

Computer Science Applications
Radiology Nuclear Medicine and imaging

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10.1016/j.compmedimag.2007.08.009

Cite this

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title = "Least-square conformal brain mapping with spring energy",

abstract = "The human brain cortex is a highly convoluted sheet. Mapping of the cortical surface into a canonical coordinate space is an important tool for the study of the structure and function of the brain. Here, we present a technique based on least-square conformal mapping with spring energy for the mapping of the cortical surface. This method aims to reduce the metric and area distortion while maintaining the conformal map and computation efficiency. We demonstrate through numerical results that this method effectively controls metric and area distortion, and is computational efficient. This technique is particularly useful for fast visualization of the brain cortex.",

keywords = "Angle distortion, Area distortion, Brain cortex, Brain mapping, Conformal mapping, Spring energy",

author = "Jingxin Nie and Tianming Liu and Gang Li and Geoffrey Young and Ashley Tarokh and Lei Guo and Wong, {Stephen T.C.}",

note = "Funding Information: Parts of the datasets and source code were provided by Dr. Lili Ju of the University of South Carolina. This research was funded by a HCNR research grant awarded to Prof. Stephen T.C. Wong. ",

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AU - Nie, Jingxin

AU - Liu, Tianming

AU - Li, Gang

AU - Young, Geoffrey

AU - Tarokh, Ashley

AU - Guo, Lei

AU - Wong, Stephen T.C.

N1 - Funding Information: Parts of the datasets and source code were provided by Dr. Lili Ju of the University of South Carolina. This research was funded by a HCNR research grant awarded to Prof. Stephen T.C. Wong.

PY - 2007/12

Y1 - 2007/12

N2 - The human brain cortex is a highly convoluted sheet. Mapping of the cortical surface into a canonical coordinate space is an important tool for the study of the structure and function of the brain. Here, we present a technique based on least-square conformal mapping with spring energy for the mapping of the cortical surface. This method aims to reduce the metric and area distortion while maintaining the conformal map and computation efficiency. We demonstrate through numerical results that this method effectively controls metric and area distortion, and is computational efficient. This technique is particularly useful for fast visualization of the brain cortex.

AB - The human brain cortex is a highly convoluted sheet. Mapping of the cortical surface into a canonical coordinate space is an important tool for the study of the structure and function of the brain. Here, we present a technique based on least-square conformal mapping with spring energy for the mapping of the cortical surface. This method aims to reduce the metric and area distortion while maintaining the conformal map and computation efficiency. We demonstrate through numerical results that this method effectively controls metric and area distortion, and is computational efficient. This technique is particularly useful for fast visualization of the brain cortex.

KW - Angle distortion

KW - Area distortion

KW - Brain cortex

KW - Brain mapping

KW - Conformal mapping

KW - Spring energy

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Least-square conformal brain mapping with spring energy

Abstract

Keywords

ASJC Scopus subject areas

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