An adaptive complex independent component analysis to analyze dynamic contrast enhanced-MRI

Hatef Mehrabian; Ian Pang; Rajiv Chopra; Anne L. Martel

doi:10.1109/ISBI.2012.6235739

An adaptive complex independent component analysis to analyze dynamic contrast enhanced-MRI

Hatef Mehrabian, Ian Pang, Rajiv Chopra, Anne L. Martel

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

4 Scopus citations

Abstract

Pharmacokinetic (PK) modeling of tumors provides information about perfusion and vascular permeability of tumors. Identifying arterial input function (AIF) is crucial in PK modeling using dynamic contrast enhanced (DCE)-MRI. An adaptive complex independent component analysis method is developed to identify and separate AIF from complex DCE-MRI data. The results are compared with a previously introduced AIF estimation method that applied ICA to magnitude DCE-MRI data. Using simulation and experimental phantom studies it is shown that using both magnitude and phase data (complex) results in a more robust and more accurate AIF measurement algorithm.

Original language	English (US)
Title of host publication	2012 9th IEEE International Symposium on Biomedical Imaging
Subtitle of host publication	From Nano to Macro, ISBI 2012 - Proceedings
Pages	1052-1055
Number of pages	4
DOIs	https://doi.org/10.1109/ISBI.2012.6235739
State	Published - 2012
Event	2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 - Barcelona, Spain Duration: May 2 2012 → May 5 2012

Publication series

Name	Proceedings - International Symposium on Biomedical Imaging
ISSN (Print)	1945-7928
ISSN (Electronic)	1945-8452

Other

Other	2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012
Country/Territory	Spain
City	Barcelona
Period	5/2/12 → 5/5/12

Keywords

Adaptive Complex ICA (AC-ICA)
Arterial Input Function (AIF)
Pharmacokinetic modeling

ASJC Scopus subject areas

Biomedical Engineering
Radiology Nuclear Medicine and imaging

Access to Document

10.1109/ISBI.2012.6235739

Cite this

Mehrabian, H., Pang, I., Chopra, R., & Martel, A. L. (2012). An adaptive complex independent component analysis to analyze dynamic contrast enhanced-MRI. In 2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 - Proceedings (pp. 1052-1055). Article 6235739 (Proceedings - International Symposium on Biomedical Imaging). https://doi.org/10.1109/ISBI.2012.6235739

An adaptive complex independent component analysis to analyze dynamic contrast enhanced-MRI. / Mehrabian, Hatef; Pang, Ian; Chopra, Rajiv et al.
2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 - Proceedings. 2012. p. 1052-1055 6235739 (Proceedings - International Symposium on Biomedical Imaging).

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

Mehrabian, H, Pang, I, Chopra, R & Martel, AL 2012, An adaptive complex independent component analysis to analyze dynamic contrast enhanced-MRI. in 2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 - Proceedings., 6235739, Proceedings - International Symposium on Biomedical Imaging, pp. 1052-1055, 2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012, Barcelona, Spain, 5/2/12. https://doi.org/10.1109/ISBI.2012.6235739

@inproceedings{35ed9ba3b48d449bbc09507a24a46bd2,

title = "An adaptive complex independent component analysis to analyze dynamic contrast enhanced-MRI",

abstract = "Pharmacokinetic (PK) modeling of tumors provides information about perfusion and vascular permeability of tumors. Identifying arterial input function (AIF) is crucial in PK modeling using dynamic contrast enhanced (DCE)-MRI. An adaptive complex independent component analysis method is developed to identify and separate AIF from complex DCE-MRI data. The results are compared with a previously introduced AIF estimation method that applied ICA to magnitude DCE-MRI data. Using simulation and experimental phantom studies it is shown that using both magnitude and phase data (complex) results in a more robust and more accurate AIF measurement algorithm.",

keywords = "Adaptive Complex ICA (AC-ICA), Arterial Input Function (AIF), Pharmacokinetic modeling",

author = "Hatef Mehrabian and Ian Pang and Rajiv Chopra and Martel, {Anne L.}",

year = "2012",

doi = "10.1109/ISBI.2012.6235739",

language = "English (US)",

isbn = "9781457718588",

series = "Proceedings - International Symposium on Biomedical Imaging",

pages = "1052--1055",

booktitle = "2012 9th IEEE International Symposium on Biomedical Imaging",

note = "2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012 ; Conference date: 02-05-2012 Through 05-05-2012",

}

TY - GEN

T1 - An adaptive complex independent component analysis to analyze dynamic contrast enhanced-MRI

AU - Mehrabian, Hatef

AU - Pang, Ian

AU - Chopra, Rajiv

AU - Martel, Anne L.

PY - 2012

Y1 - 2012

N2 - Pharmacokinetic (PK) modeling of tumors provides information about perfusion and vascular permeability of tumors. Identifying arterial input function (AIF) is crucial in PK modeling using dynamic contrast enhanced (DCE)-MRI. An adaptive complex independent component analysis method is developed to identify and separate AIF from complex DCE-MRI data. The results are compared with a previously introduced AIF estimation method that applied ICA to magnitude DCE-MRI data. Using simulation and experimental phantom studies it is shown that using both magnitude and phase data (complex) results in a more robust and more accurate AIF measurement algorithm.

AB - Pharmacokinetic (PK) modeling of tumors provides information about perfusion and vascular permeability of tumors. Identifying arterial input function (AIF) is crucial in PK modeling using dynamic contrast enhanced (DCE)-MRI. An adaptive complex independent component analysis method is developed to identify and separate AIF from complex DCE-MRI data. The results are compared with a previously introduced AIF estimation method that applied ICA to magnitude DCE-MRI data. Using simulation and experimental phantom studies it is shown that using both magnitude and phase data (complex) results in a more robust and more accurate AIF measurement algorithm.

KW - Adaptive Complex ICA (AC-ICA)

KW - Arterial Input Function (AIF)

KW - Pharmacokinetic modeling

UR - http://www.scopus.com/inward/record.url?scp=84864843671&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84864843671&partnerID=8YFLogxK

U2 - 10.1109/ISBI.2012.6235739

DO - 10.1109/ISBI.2012.6235739

M3 - Conference contribution

AN - SCOPUS:84864843671

SN - 9781457718588

T3 - Proceedings - International Symposium on Biomedical Imaging

SP - 1052

EP - 1055

BT - 2012 9th IEEE International Symposium on Biomedical Imaging

T2 - 2012 9th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2012

Y2 - 2 May 2012 through 5 May 2012

ER -

An adaptive complex independent component analysis to analyze dynamic contrast enhanced-MRI

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this