Accuracy of the Morphology Enabled Dipole Inversion (MEDI) Algorithm for Quantitative Susceptibility Mapping in MRI

Tian Liu; Weiyu Xu; Pascal Spincemaille; A. Salman Avestimehr; Yi Wang

doi:10.1109/TMI.2011.2182523

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Accuracy of the Morphology Enabled Dipole Inversion (MEDI) Algorithm for Quantitative Susceptibility Mapping in MRI

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Accuracy of the Morphology Enabled Dipole Inversion (MEDI) Algorithm for Quantitative Susceptibility Mapping in MRI

Tian Liu, Weiyu Xu, Pascal Spincemaille, A. Salman Avestimehr and Yi Wang

IEEE transactions on medical imaging, Vol.31(3), pp.816-824

03/2012

DOI: 10.1109/TMI.2011.2182523

PMCID: PMC3613569

PMID: 22231170

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https://www.ncbi.nlm.nih.gov/pmc/articles/3613569View

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Abstract

Determining the susceptibility distribution from the magnetic field measured in a magnetic resonance (MR) scanner is an ill-posed inverse problem, because of the presence of zeroes in the convolution kernel in the forward problem. An algorithm called morphology enabled dipole inversion (MEDI), which incorporates spatial prior information, has been proposed to generate a quantitative susceptibility map (QSM). The accuracy of QSM can be validated experimentally. However, there is not yet a rigorous mathematical demonstration of accuracy for a general regularized approach or for MEDI specifically. The error in the susceptibility map reconstructed by MEDI is expressed in terms of the acquisition noise and the error in the spatial prior information. A detailed analysis demonstrates that the error in the susceptibility map reconstructed by MEDI is bounded by a linear function of these two error sources. Numerical analysis confirms that the error of the susceptibility map reconstructed by MEDI is on the same order of the noise in the original MRI data, and comprehensive edge detection will lead to reduced model error in MEDI. Additional phantom validation and human brain imaging demonstrated the practicality of the MEDI method.

magnetic resonance imaging (MRI)

quantitative susceptibility mapping

Error analysis

morphology enabled dipoleinversion (MEDI)

Details

Title: Subtitle: Accuracy of the Morphology Enabled Dipole Inversion (MEDI) Algorithm for Quantitative Susceptibility Mapping in MRI
Creators: Tian Liu - Department of Biomedical Engineering, Cornell University, Ithaca, NY 14853 USA
Weiyu Xu - Department of Electrical Engineering, Cornell University, Ithaca, NY 14853 USA
Pascal Spincemaille - Department of Radiology, Weill Cornell Medical College, New York, NY 10065 USA
A. Salman Avestimehr - Department of Electrical Engineering, Cornell University, Ithaca, NY 14853 USA
Yi Wang - Department of Biomedical Engineering, Cornell University, Ithaca, NY 14853 USA, and with the Department of Radiology, Weill Cornell Medical College, New York, NY 10065 USA, Department of Biomedical Engineering, Kyung Hee University, Seoul 130-701, Korea
Resource Type: Journal article
Publication Details: IEEE transactions on medical imaging, Vol.31(3), pp.816-824
DOI: 10.1109/TMI.2011.2182523
PMID: 22231170
PMCID: PMC3613569
NLM abbreviation: IEEE Trans Med Imaging
ISSN: 0278-0062
eISSN: 1558-254X
Publisher: Institute of Electrical and Electronics Engineers
Grant note: R01 NS072370 || NS / National Institute of Neurological Disorders and Stroke : NINDS R01 EB013443 || EB / National Institute of Biomedical Imaging and Bioengineering : NIBIB
Language: English
Date published: 03/2012
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984083294102771

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