摘要：Automatic estimation of current dipoles from biomagnetic data is
still a problematic task. This is due not only to the ill-posedness of
the inverse problem but also to two intrinsic difficulties introduced by
the dipolar model: the unknown number of sources and the nonlinear
relationship between the source locations and the data. Recently, we
have developed a new Bayesian approach, particle filtering, based on
dynamical tracking of the dipole constellation. Contrary to many
dipole-based methods, particle filtering does not assume stationarity
of the source configuration: the number of dipoles and their positions
are estimated and updated dynamically during the course of the MEG
sequence. We have now developed a Matlab-based graphical user interface,
which allows nonexpert users to do automatic dipole estimation
from MEG data with particle filtering. In the present paper, we describe
the main features of the software and show the analysis of both
a synthetic data set and an experimental dataset.
