Physiological system identification with the Kalman filter in diffuse optical tomography

Med Image Comput Comput Assist Interv. 2005;8(Pt 2):649-56. doi: 10.1007/11566489_80.

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.

Publication types

  • Evaluation Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Artificial Intelligence
  • Computer Simulation
  • Connective Tissue / physiology*
  • Connective Tissue / ultrastructure*
  • Humans
  • Image Interpretation, Computer-Assisted / methods
  • Magnetic Resonance Imaging / methods*
  • Male
  • Models, Biological*
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Systems Theory
  • Tomography, Optical / methods*