Efficient and robust estimation of blood oxygenation levels in single cerebral veins.
Blood oxygenation level is an important measure that can be used alongside functional magnetic resonance imaging data in order to obtain closer correlates of neuronal activation. A robust estimate of this measure has thus far not been demonstrated. This is mainly due to the lack of knowledge of the...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 50; no. 5; pp. 473 - 483 |
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| Autores principales: | , , , |
| Formato: | research Journal Article |
| Publicado: |
Springer Nature
May2012
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104558674&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104558674 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: May2012 vid: 50 iid: 5 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104558674 NLM22415740 2011535468 10.1007/s11517-012-0886-8 NLM22415740 PMC3618887 104558674 ppf: 473 ppct: 10 formats: fmt: @attributes: type: P tig: atl: Efficient and robust estimation of blood oxygenation levels in single cerebral veins. aug: au: Dagher J Du YP Dagher, Joseph Du, Yiping P affil: Department of Psychiatry, Brain Imaging Center, School of Medicine, University of Colorado, Denver, CO 80045, USA sug: subj: Cerebral Veins Physiology Models, Biological Oxygen Blood Algorithms Cerebrovascular Circulation Physiology Human Magnetic Resonance Imaging Methods Signal Processing, Computer Assisted ab: Blood oxygenation level is an important measure that can be used alongside functional magnetic resonance imaging data in order to obtain closer correlates of neuronal activation. A robust estimate of this measure has thus far not been demonstrated. This is mainly due to the lack of knowledge of the underlying parameters which influence the numerical estimates of blood oxygenation. In this paper, we present a systematic analysis of the estimation performance of venous hemoglobin oxygen saturation [Formula: see text] as a function of noise, physiologic and geometric parameters. Furthermore, we present a novel algorithm for estimating [Formula: see text] from the temporal decay of an MR signal. The proposed algorithm incorporates prior information about the functional dependence between [Formula: see text] and relaxation rates. We compare our algorithm to an existing method in the literature and analyze the estimation performance. We show that our proposed algorithm is more efficient, achieving gains in performance as high as 92 %. We also show how our estimation algorithm takes advantage of signal features that are specific to the underlying physiology and geometry. We argue that optimal acquisition sequences, and corresponding estimation methods, should take into account such features in order to obtain robust estimates of blood oxygenation. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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