Automatic parameter optimization for de-noising MR data

  • Authors:
  • Joaquín Castellanos;Karl Rohr;Thomas Tolxdorff;Gudrun Wagenknecht

  • Affiliations:
  • Central Institute for Electronics, Research Center Jülich, Germany;Dept. Intelligent Bioinformatics Systems IPMB, University of Heidelberg and DKFZ Heidelberg, Germany;Institute of Medical Informatics, Biostatistics and Epidemiology, Charité - University Medicine Berlin, Germany;Central Institute for Electronics, Research Center Jülich, Germany

  • Venue:
  • MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
  • Year:
  • 2005

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Abstract

This paper describes an automatic parameter optimization method for anisotropic diffusion filters used to de-noise 2D and 3D MR images. The filtering process is integrated into a closed-loop system where image improvement is monitored indirectly by comparing the characteristics of the suppressed noise with those of the assumed noise model at the optimal point. In order to verify the performance of this approach, experimental results obtained with this method are presented together with the results obtained by median and k-nearest neighbor filters.