Title :
Probabilistic modeling of single-trial fMRI data
Author :
Svensén, Markus ; Kruggel, Frithjof ; Von Cramon, D. Yves
Author_Institution :
Max-Planck Inst. of Cognitive Neurosci., Leipzig, Germany
Abstract :
Describes a probabilistic framework for modeling single-trial functional magnetic resonance (fMR) images based on a parametric model for the hemodynamic response and Markov random field (MRF) image models. The model is fitted to image data by maximizing a lower bound on the log likelihood. The result is an approximate maximum a posteriori estimate of the joint distribution over the model parameters and pixel labels. Examples show how this technique can used to segment two-dimensional (2-D) fMR images, or parts thereof, into regions with different characteristics of their hemodynamic response.
Keywords :
biomedical MRI; brain models; haemodynamics; image segmentation; medical image processing; Markov random field image models; approximate maximum a posteriori estimate; hemodynamic response; joint distribution; log likelihood; model parameters; parametric model; pixel labels; probabilistic modeling; single-trial fMRI data; single-trial functional magnetic resonance images; Blood; Delay; Hemodynamics; Image segmentation; Magnetic field measurement; Magnetic resonance; Markov random fields; Parameter estimation; Parametric statistics; Performance evaluation; Brain; Computer Simulation; Hemodynamics; Humans; Image Processing, Computer-Assisted; Likelihood Functions; Magnetic Resonance Imaging; Markov Chains; Models, Statistical; Phantoms, Imaging;
Journal_Title :
Medical Imaging, IEEE Transactions on
