Predictive modeling of anatomic structures using canonical correlation analysis

Tianming Liu; Dinggang Shen; Christos Davatzikos

Predictive modeling of anatomic structures using canonical correlation analysis

Tianming Liu^*
, Dinggang Shen
, Christos Davatzikos

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

20 Citations (Scopus)

Abstract

In this paper, we present a method for predictive modeling of anatomic structures using canonical correlation analysis (CCA). Using this technique, certain anatomical structures, such as tumor-distorted structures, can be estimated from others by exploring the correlation between them, which has been determined from a set of training samples. Cortical surfaces and corpus callosum boundaries have been used to demonstrate the performance of the proposed method in predictive modeling. Applications of this method are in estimating brain tissues obscured by tumors and surrounding edema, in detecting abnormal structures, and in formulating alternate forms of statistically-based interpolation and regularization.

Original language	English
Title of host publication	2004 2nd IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	Macro to Nano
Pages	1279-1282
Number of pages	4
Publication status	Published - 2004
Event	2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano - Arlington, VA, United States Duration: 2004 Apr 15 → 2004 Apr 18

Publication series

Name	2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano
Volume	2

Other

Other	2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano
Country/Territory	United States
City	Arlington, VA
Period	04/4/15 → 04/4/18

ASJC Scopus subject areas

General Engineering

Cite this

Predictive modeling of anatomic structures using canonical correlation analysis. / Liu, Tianming; Shen, Dinggang; Davatzikos, Christos.
2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano. 2004. p. 1279-1282 (2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Liu, T, Shen, D & Davatzikos, C 2004, Predictive modeling of anatomic structures using canonical correlation analysis. in 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano. 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano, vol. 2, pp. 1279-1282, 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano, Arlington, VA, United States, 04/4/15.

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AB - In this paper, we present a method for predictive modeling of anatomic structures using canonical correlation analysis (CCA). Using this technique, certain anatomical structures, such as tumor-distorted structures, can be estimated from others by exploring the correlation between them, which has been determined from a set of training samples. Cortical surfaces and corpus callosum boundaries have been used to demonstrate the performance of the proposed method in predictive modeling. Applications of this method are in estimating brain tissues obscured by tumors and surrounding edema, in detecting abnormal structures, and in formulating alternate forms of statistically-based interpolation and regularization.

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M3 - Conference contribution

AN - SCOPUS:17144416167

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SN - 9780780383883

T3 - 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano

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BT - 2004 2nd IEEE International Symposium on Biomedical Imaging

T2 - 2004 2nd IEEE International Symposium on Biomedical Imaging: Macro to Nano

Y2 - 15 April 2004 through 18 April 2004

ER -

Predictive modeling of anatomic structures using canonical correlation analysis

Abstract

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ASJC Scopus subject areas

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