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Publication Detail
Physiological system identification with the Kalman filter in diffuse optical tomography
  • Publication Type:
    Conference
  • Authors:
    Diamond SG, Huppert TJ, Kolehmainen V, Franceschini MA, Kaipio JP, Arridge SR, Boas DA
  • Publication date:
    01/12/2005
  • Pagination:
    649, 656
  • Published proceedings:
    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
  • Volume:
    3750 LNCS
  • ISBN-10:
    3540293264
  • ISBN-13:
    9783540293262
  • Status:
    Published
  • Print ISSN:
    0302-9743
Abstract
Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxy- and deoxyhemoglobin. When applied to functional neuroimaging, DOT measures hemodynamics in the scalp and brain that reflect competing metabolic demands and cardiovascular dynamics. Separating the effects of systemic cardiovascular regulation from the local dynamics is vitally important in DOT analysis. In this paper, we use auxiliary physiological measurements such as blood pressure and heart rate within a Kalman filter framework to model physiological components in DOT. We validate the method on data from a human subject with simulated local hemodynamic responses added to the baseline physiology. The proposed method significantly improved estimates of the local hemodynamics in this test case. Cardiovascular dynamics also affect the blood oxygen dependent (BOLD) signal in functional magnetic resonance imaging (fMRI). This Kalman filter framework for DOT may be adapted for BOLD fMRI analysis and multimodal studies. © Springer-Verlag Berlin Heidelberg 2005.
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