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.
Chapter PDF
Similar content being viewed by others
Keywords
- Heart Rate Variability
- Functional Response
- Respiratory Sinus Arrhythmia
- Functional Neuroimaging
- Bold fMRI
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Gibson, A.P., Hebden, J., Arridge, S.: Recent advances in diffuse optical imaging. Phys. Med. Biol. 50, 1–43 (2005)
Strangman, G., Culver, J., Thompson, J., Boas, D.: A quantitative comparison of simultaneous bold fMRI and NIRS recordings during functional brain activation. NeuroImage 17, 719–731 (2002)
Kolehmainen, V., Prince, S., Arridge, S., Kaipio, J.: State-estimation approach to the nonstationary optical tomography problem. J. Opt. Soc. Am. A 20, 876–889 (2003)
Prince, S., Kolehmainen, V., Kaipio, J., Franceschini, M., Boas, D., Arridge, S.: Time-series estimation of biological factors in optical diffusion tomography. Phys. Med. Biol. 48, 1491–1504 (2003)
Zhang, Y., Brooks, D., Franceschini, M., Boas, D.: Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging. Journal of Biomedical Optics 10, 011014–1–11 (2005)
Cohen, M.A., Taylor, J.A.: Short-term cardiovascular oscillations in man: measuring and modelling the physiologies. Journal of Physiology 542(3), 669–683 (2002)
Frackowiak, R., Friston, K., Frith, C., Dolan, R., Price, C., Zeki, S., Ashburner, J., Penny, W. (eds.): Human Brain Function, 2nd edn. Academic Press, London (2003)
Roche, A., Pinel, P., Dehaene, S., Poline, J.: Solving incrementally the fitting and detection problems in fMRI time series. In: Barillot, C., Haynor, D.R., Hellier, P. (eds.) MICCAI 2004, Part 2. LNCS, vol. 3217, pp. 719–726. Springer, Heidelberg (2004)
Kalman, R.: A new approach to linear filtering and prediction problems. Trans. of the ASME–Journal of Basic Engineering 82, 35–45 (1960)
Arridge, S., Cope, M., Delpy, D.: The theoretical basis for the determination of optical pathlengths in tissue: temporal and frequency analysis. Phys. Med. Biol. 37, 1531–1560 (1992)
Franceschini, M., Fantini, S., Thompson, J., Culver, J., Boas, D.: Hemodynamic evoked response of the sensorimotor cortex measured non-invasively with near-infrared optical imaging. Psychophysiology 40, 548–560 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Diamond, S.G. et al. (2005). Physiological System Identification with the Kalman Filter in Diffuse Optical Tomography. In: Duncan, J.S., Gerig, G. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005. MICCAI 2005. Lecture Notes in Computer Science, vol 3750. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11566489_80
Download citation
DOI: https://doi.org/10.1007/11566489_80
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29326-2
Online ISBN: 978-3-540-32095-1
eBook Packages: Computer ScienceComputer Science (R0)