Adaptive image segmentation for robust measurement of longitudinal brain tissue change

Evan Fletcher, Baljeet Singh, Danielle J Harvey, Owen Carmichael, Charles DeCarli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

30 Scopus citations

Abstract

We present a method that significantly improves magnetic resonance imaging (MRI) based brain tissue segmentation by modeling the topography of boundaries between tissue compartments. Edge operators are used to identify tissue interfaces and thereby more realistically model tissue label dependencies between adjacent voxels on opposite sides of an interface. When applied to a synthetic MRI template corrupted by additive noise, it provided more consistent tissue labeling across noise levels than two commonly used methods (FAST and SPM5). When applied to longitudinal MRI series it provided lesser variability in individual trajectories of tissue change, suggesting superior ability to discriminate real tissue change from noise. These results suggest that this method may be useful for robust longitudinal brain tissue change estimation.

Original languageEnglish (US)
Title of host publicationProceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Pages5319-5322
Number of pages4
DOIs
StatePublished - 2012
Event34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012 - San Diego, CA, United States
Duration: Aug 28 2012Sep 1 2012

Other

Other34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2012
CountryUnited States
CitySan Diego, CA
Period8/28/129/1/12

ASJC Scopus subject areas

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

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  • Cite this

    Fletcher, E., Singh, B., Harvey, D. J., Carmichael, O., & DeCarli, C. (2012). Adaptive image segmentation for robust measurement of longitudinal brain tissue change. In Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS (pp. 5319-5322). [6347195] https://doi.org/10.1109/EMBC.2012.6347195