Real-time MR diffusion tensor and Q-ball imaging using Kalman filtering

Med Image Comput Comput Assist Interv. 2007;10(Pt 1):27-35. doi: 10.1007/978-3-540-75757-3_4.

Abstract

Magnetic resonance diffusion imaging (dMRI) has become an established research tool for the investigation of tissue structure and orientation. In this paper, we present a method for real time processing of diffusion tensor and Q-ball imaging. The basic idea is to use Kalman filtering framework to fit either the linear tensor or Q-ball model. Because the Kalman filter is designed to be an incremental algorithm, it naturally enables updating the model estimate after the acquisition of any new diffusion-weighted volume. Processing diffusion models and maps during ongoing scans provides a new useful tool for clinicians, especially when it is not possible to predict how long a subject may remain still in the magnet.

MeSH terms

  • Algorithms
  • Brain / anatomy & histology*
  • Computer Simulation
  • Computer Systems
  • Diffusion Magnetic Resonance Imaging / methods*
  • Image Enhancement / methods*
  • Image Interpretation, Computer-Assisted / methods*
  • Imaging, Three-Dimensional / methods*
  • Models, Neurological
  • Models, Statistical
  • Nerve Fibers, Myelinated / ultrastructure*
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Sensitivity and Specificity
  • Signal Processing, Computer-Assisted