Adaptive smoothing strategies to eliminate the scalp/ventricle artifact in statistical parametric mapping

Lan Lin, Kewei Chen, G. E. Alexander, Jiping He, Eric M. Reiman

Research output: Contribution to journalConference articlepeer-review


In positron emission tomographic (PET) or magnetic resonance imaging (MRI) neuroimaging studies, spatial smoothing technique is commonly applied to increase the signal to noise ratio and to condition neoroimaging data for subsequent statistical analysis, and to reduce errors associated with registration or spatial normalizations. Usually, the smoothing step is applied to the images without any masking. Thus, some artifacts adjacent but outside of the brain will enter the brain volume. Masking the brain volume before smoothing has been suggested as one way to eliminate the introduced artifact, but it will introduce zero-in (intensities within-mask voxels are reduced) and nonzero-out (intensities outside the mask become non-zero) artifacts. Here we proposed an adaptive smoothing method to reduce the influence of such artifacts. Unlike the conventional smoothing method, the adaptive strategy did not introduce artificial addition (due to nonzero-out artifact) and deletion (due to zero-in), suggesting that such adaptive smoothing methods may be helpful in reducing the influence of non-brain tissue in the analysis of neuroimaging data.

Original languageEnglish (US)
Pages (from-to)1039-1040
Number of pages2
JournalAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
StatePublished - 2002
EventProceedings of the 2002 IEEE Engineering in Medicine and Biology 24th Annual Conference and the 2002 Fall Meeting of the Biomedical Engineering Society (BMES / EMBS) - Houston, TX, United States
Duration: Oct 23 2002Oct 26 2002


  • Artifact
  • Neuroimaging
  • Smoothing
  • Statistical analysis

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics


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