Performance of a minimum-support imaging method for biomagnetic source localization

S. S. Nagarajan, O. Portniaguine, K. Sekihara, D. Hwang, C. Johnson

Research output: Contribution to journalConference article

1 Citation (Scopus)

Abstract

Images of brain activation typically comprise of small patches of activation with large regions of non-activation. Such images can be considered as minimum support images, where non-zero values occupy only a small area. In this paper, we propose a new minimum support imaging method that solves the bio-electromagnetic inverse problem. We formulate the problem using Lead-fields under Tikhonov theory which replaces the original ill-posed inverse problem by a well-posed minimization of a Tikhonov parametric functional consisting of a sum of the misfit and stabilizer functions. The stabilizer function embeds apriori assumptions about brain activation, which we assume is minimum-support. We illustrate the proposed method in simulations. Using realistic head and sensor geometry, we generate forward model MEG data for multiple-dipole sources. This simulated forward model data with additive noise was used to perform data inversion. Monte Carlo simulations indicate that the accuracy in localization of single dipoles is 2.1 mm for low noise conditions. While this performance is consistent with performance of conventional parametric dipole inversion, the minimum support method is capable of reconstructing multiple distributed sources.

Original languageEnglish
Pages (from-to)2006-2007
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume3
Publication statusPublished - 2002 Dec 1
EventProceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) - Houston, TX, United States
Duration: 2002 Oct 232002 Oct 26

Fingerprint

Chemical activation
Inverse problems
Imaging techniques
Noise
Brain
Additive noise
Electromagnetic Phenomena
Lead
Head
Geometry
Sensors
Monte Carlo simulation

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

Cite this

@article{8ce46bade7de4cb6a6035380b5bb3dcf,
title = "Performance of a minimum-support imaging method for biomagnetic source localization",
abstract = "Images of brain activation typically comprise of small patches of activation with large regions of non-activation. Such images can be considered as minimum support images, where non-zero values occupy only a small area. In this paper, we propose a new minimum support imaging method that solves the bio-electromagnetic inverse problem. We formulate the problem using Lead-fields under Tikhonov theory which replaces the original ill-posed inverse problem by a well-posed minimization of a Tikhonov parametric functional consisting of a sum of the misfit and stabilizer functions. The stabilizer function embeds apriori assumptions about brain activation, which we assume is minimum-support. We illustrate the proposed method in simulations. Using realistic head and sensor geometry, we generate forward model MEG data for multiple-dipole sources. This simulated forward model data with additive noise was used to perform data inversion. Monte Carlo simulations indicate that the accuracy in localization of single dipoles is 2.1 mm for low noise conditions. While this performance is consistent with performance of conventional parametric dipole inversion, the minimum support method is capable of reconstructing multiple distributed sources.",
author = "Nagarajan, {S. S.} and O. Portniaguine and K. Sekihara and D. Hwang and C. Johnson",
year = "2002",
month = "12",
day = "1",
language = "English",
volume = "3",
pages = "2006--2007",
journal = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",
issn = "1557-170X",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

Performance of a minimum-support imaging method for biomagnetic source localization. / Nagarajan, S. S.; Portniaguine, O.; Sekihara, K.; Hwang, D.; Johnson, C.

In: Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings, Vol. 3, 01.12.2002, p. 2006-2007.

Research output: Contribution to journalConference article

TY - JOUR

T1 - Performance of a minimum-support imaging method for biomagnetic source localization

AU - Nagarajan, S. S.

AU - Portniaguine, O.

AU - Sekihara, K.

AU - Hwang, D.

AU - Johnson, C.

PY - 2002/12/1

Y1 - 2002/12/1

N2 - Images of brain activation typically comprise of small patches of activation with large regions of non-activation. Such images can be considered as minimum support images, where non-zero values occupy only a small area. In this paper, we propose a new minimum support imaging method that solves the bio-electromagnetic inverse problem. We formulate the problem using Lead-fields under Tikhonov theory which replaces the original ill-posed inverse problem by a well-posed minimization of a Tikhonov parametric functional consisting of a sum of the misfit and stabilizer functions. The stabilizer function embeds apriori assumptions about brain activation, which we assume is minimum-support. We illustrate the proposed method in simulations. Using realistic head and sensor geometry, we generate forward model MEG data for multiple-dipole sources. This simulated forward model data with additive noise was used to perform data inversion. Monte Carlo simulations indicate that the accuracy in localization of single dipoles is 2.1 mm for low noise conditions. While this performance is consistent with performance of conventional parametric dipole inversion, the minimum support method is capable of reconstructing multiple distributed sources.

AB - Images of brain activation typically comprise of small patches of activation with large regions of non-activation. Such images can be considered as minimum support images, where non-zero values occupy only a small area. In this paper, we propose a new minimum support imaging method that solves the bio-electromagnetic inverse problem. We formulate the problem using Lead-fields under Tikhonov theory which replaces the original ill-posed inverse problem by a well-posed minimization of a Tikhonov parametric functional consisting of a sum of the misfit and stabilizer functions. The stabilizer function embeds apriori assumptions about brain activation, which we assume is minimum-support. We illustrate the proposed method in simulations. Using realistic head and sensor geometry, we generate forward model MEG data for multiple-dipole sources. This simulated forward model data with additive noise was used to perform data inversion. Monte Carlo simulations indicate that the accuracy in localization of single dipoles is 2.1 mm for low noise conditions. While this performance is consistent with performance of conventional parametric dipole inversion, the minimum support method is capable of reconstructing multiple distributed sources.

UR - http://www.scopus.com/inward/record.url?scp=0036911466&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0036911466&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:0036911466

VL - 3

SP - 2006

EP - 2007

JO - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

JF - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

SN - 1557-170X

ER -