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Special Issue on Signal Processing Aspects of Brain Imaging
September 2005
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Recent developments in measurement devices have made it possible to monitor very small time varying physiological changes in the working human brain using dedicated sensitive physical measurement principles. These devices include EEG/MEG, EIT, fMRI and PET, as well as combinations of EEG/fMRI, EEG/PET. These techniques have tremendously increased our knowledge of the human brain and provided new diagnosis techniques in clinical applications. They have also given rise to new fundamental problems in statistics and signal processing, which commonly exist in the different imaging modalities. Examples of the earliest solutions that originated from the signal processing community are MUSIC, beamforming techniques and (non-linear) parameter estimation algorithms.
A similar scientific and technological development can be depicted for other physiological measurements, using the same equipment. We solicit papers dealing with brain imaging aspects using different modalities and signal processing solutions. Papers dealing with other physiological signals are also encouraged. The goal is to extract the most reliable and relevant information from the raw data given hardware specifications.
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•Reconstruction or source localization problems.
•Integration of results obtained with different techniques into a single model.
•Modeling and estimation of phenomena like habituation effects, etc.
•The question of whether, where and when two time varying data sets are statistically significantly different (thereby accounting for the multiple comparison problem).
•Treatment of spatially and temporally correlated background noise.
•The question of whether different parts of the brain are (non-linearly) correlated.
•Computation of (non-linear) correlations between electric/heamodynamic brain sources.
•The problem of the physiological interpretation of these signals.
•Artefact removal problem.
•Time/frequency analysis.
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| Guest
Editors: |
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• Matti Hämäläinen, A.A. Martinos Center for Biomedical Imaging, Boston, USA, msh@nmr.mgh.harvard.edu
• Guido Nolte, National Institute of Health, Bethesda, USA, nolte@cs.unm.edu
• Michael Scherg, University Hostpital Heidelberg, Germany, MScherg@besa.de
• Keith Worsly, McGill University Montreal, Canada, worsley@math.mcgill.ca
• Jan C. de Munck (lead GE), VU Medical Center, Amsterdam, The Netherlands, Jc.munck@vumc.nl |
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