Particle filtering for nonlinear BOLD signal analysis

Leigh A. Johnston; Eugene Duff; Gary F. Egan

Particle filtering for nonlinear BOLD signal analysis

Leigh A. Johnston, Eugene Duff, Gary F. Egan

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

Abstract

Functional Magnetic Resonance imaging studies analyse sequences of brain volumes whose intensity changes predominantly reflect blood oxygenation level dependent (BOLD) effects. The most comprehensive signal model to date of the BOLD effect is formulated as a continuous-time system of nonlinear stochastic differential equations. In this paper we present a particle filtering method for the analysis of the BOLD system, and demonstrate it to be both accurate and robust in estimating the hidden physiological states including cerebral blood flow, cerebral blood volume, total deoxyhemoglobin content, and the flow inducing signal, from functional imaging data.

Original language	English
Title of host publication	Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006
Subtitle of host publication	9th International Conference Copenhagen, Denmark, October 1-6, 2006 Proceedings, Part II
Editors	Rasmus Larsen, Mads Nielsen, Jon Sporring
Place of Publication	Berlin Germany
Publisher	Springer
Pages	292-299
Number of pages	8
ISBN (Print)	354044727X, 9783540447276
Publication status	Published - 1 Dec 2006
Externally published	Yes
Event	Medical Image Computing and Computer-Assisted Intervention 2006 - Copenhagen, Denmark Duration: 1 Oct 2006 → 6 Oct 2006 Conference number: 9th https://link.springer.com/book/10.1007/11866565 (Proceedings)

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	4191
ISSN (Print)	0302-9743

Conference

Conference	Medical Image Computing and Computer-Assisted Intervention 2006
Abbreviated title	MICCAI 2006
Country/Territory	Denmark
City	Copenhagen
Period	1/10/06 → 6/10/06
Internet address	https://link.springer.com/book/10.1007/11866565 (Proceedings)

Cite this

Johnston, L. A., Duff, E., & Egan, G. F. (2006). Particle filtering for nonlinear BOLD signal analysis. In R. Larsen, M. Nielsen, & J. Sporring (Eds.), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006: 9th International Conference Copenhagen, Denmark, October 1-6, 2006 Proceedings, Part II (pp. 292-299). (Lecture Notes in Computer Science; Vol. 4191). Springer.

Johnston, Leigh A. ; Duff, Eugene ; Egan, Gary F. / Particle filtering for nonlinear BOLD signal analysis. Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006: 9th International Conference Copenhagen, Denmark, October 1-6, 2006 Proceedings, Part II. editor / Rasmus Larsen ; Mads Nielsen ; Jon Sporring. Berlin Germany : Springer, 2006. pp. 292-299 (Lecture Notes in Computer Science).

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abstract = "Functional Magnetic Resonance imaging studies analyse sequences of brain volumes whose intensity changes predominantly reflect blood oxygenation level dependent (BOLD) effects. The most comprehensive signal model to date of the BOLD effect is formulated as a continuous-time system of nonlinear stochastic differential equations. In this paper we present a particle filtering method for the analysis of the BOLD system, and demonstrate it to be both accurate and robust in estimating the hidden physiological states including cerebral blood flow, cerebral blood volume, total deoxyhemoglobin content, and the flow inducing signal, from functional imaging data.",

author = "Johnston, {Leigh A.} and Eugene Duff and Egan, {Gary F.}",

year = "2006",

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booktitle = "Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006",

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Johnston, LA, Duff, E & Egan, GF 2006, Particle filtering for nonlinear BOLD signal analysis. in R Larsen, M Nielsen & J Sporring (eds), Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006: 9th International Conference Copenhagen, Denmark, October 1-6, 2006 Proceedings, Part II. Lecture Notes in Computer Science, vol. 4191, Springer, Berlin Germany, pp. 292-299, Medical Image Computing and Computer-Assisted Intervention 2006, Copenhagen, Denmark, 1/10/06.

Particle filtering for nonlinear BOLD signal analysis. / Johnston, Leigh A.; Duff, Eugene; Egan, Gary F.

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006: 9th International Conference Copenhagen, Denmark, October 1-6, 2006 Proceedings, Part II. ed. / Rasmus Larsen; Mads Nielsen; Jon Sporring. Berlin Germany : Springer, 2006. p. 292-299 (Lecture Notes in Computer Science; Vol. 4191).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

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AU - Egan, Gary F.

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AB - Functional Magnetic Resonance imaging studies analyse sequences of brain volumes whose intensity changes predominantly reflect blood oxygenation level dependent (BOLD) effects. The most comprehensive signal model to date of the BOLD effect is formulated as a continuous-time system of nonlinear stochastic differential equations. In this paper we present a particle filtering method for the analysis of the BOLD system, and demonstrate it to be both accurate and robust in estimating the hidden physiological states including cerebral blood flow, cerebral blood volume, total deoxyhemoglobin content, and the flow inducing signal, from functional imaging data.

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SN - 354044727X

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T3 - Lecture Notes in Computer Science

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BT - Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006

A2 - Larsen, Rasmus

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T2 - Medical Image Computing and Computer-Assisted Intervention 2006

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Johnston LA, Duff E, Egan GF. Particle filtering for nonlinear BOLD signal analysis. In Larsen R, Nielsen M, Sporring J, editors, Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006: 9th International Conference Copenhagen, Denmark, October 1-6, 2006 Proceedings, Part II. Berlin Germany: Springer. 2006. p. 292-299. (Lecture Notes in Computer Science).

Particle filtering for nonlinear BOLD signal analysis

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