Publication Type Academic Article
Authors Tabelow K, Polzehl J, Ulug A, Dyke J, Watts R, Heier L, Voss H
Journal IEEE Trans Med Imaging
Volume 27
Issue 4
Pagination 531-7
Date Published 04/01/2008
ISSN 1558-254X
Keywords Algorithms, Brain Mapping, Brain Neoplasms, Imaging, Three-Dimensional, Magnetic Resonance Imaging, Pattern Recognition, Automated
Abstract An important problem of the analysis of functional magnetic resonance imaging (fMRI) experiments is to achieve some noise reduction of the data without blurring the shape of the activation areas. As a novel solution to this problem, recently the propagation-separation (PS) approach has been proposed. PS is a structure adaptive smoothing method that adapts to different shapes of activation areas. In this paper, we demonstrate how this method results in a more accurate localization of brain activity. First, it is shown in numerical simulations that PS is superior over Gaussian smoothing with respect to the accurate description of the shape of activation clusters and results in less false detections. Second, in a study of 37 presurgical planning cases we found that PS and Gaussian smoothing often yield different results, and we present examples showing aspects of the superiority of PS as applied to presurgical planning.
DOI 10.1109/TMI.2007.908684
PubMed ID 18390349
Back to Top