Accurate localization of brain activity in presurgical FMRI by structure adaptive smoothing. Academic Article uri icon

Overview

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.

publication date

  • April 1, 2008

Research

keywords

  • Algorithms
  • Brain Mapping
  • Brain Neoplasms
  • Imaging, Three-Dimensional
  • Magnetic Resonance Imaging
  • Pattern Recognition, Automated

Identity

Scopus Document Identifier

  • 41649119421

Digital Object Identifier (DOI)

  • 10.1109/TMI.2007.908684

PubMed ID

  • 18390349

Additional Document Info

volume

  • 27

issue

  • 4