MR cranial image segmentation - a morphological and clustering approach

Te shen Liang, Jeffrey J. Rodriguez

Research output: Contribution to conferencePaper

1 Scopus citations

Abstract

Computer-aided visualization of the brain surface has numerous applications in structural and functional brain mapping for neuroscience, as well as in surgical path planning. Surface visualization of the brain using magnetic resonance (MR) images requires pixels in the images to be discriminated, or segmented into various tissue types. In this work, an automated and efficient method, based on mathematical morphology and unsupervised clustering analysis, is proposed for segmenting 3-D MR images of the human head. The proposed method provides better rendered views of the brain surface with much less computation time, compared to a previous, direct fuzzy-based approach. The resulting rendered views of the brain surface are shown, as well as the efficiency and error analysis of the proposed methodology.

Original languageEnglish (US)
Pages184-189
Number of pages6
StatePublished - Jan 1 1996
EventProceedings of the 1996 IEEE Southwest Symposium on Image Analysis and Interpretation - San Antonio, TX, USA
Duration: Apr 8 1996Apr 9 1996

Other

OtherProceedings of the 1996 IEEE Southwest Symposium on Image Analysis and Interpretation
CitySan Antonio, TX, USA
Period4/8/964/9/96

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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    Liang, T. S., & Rodriguez, J. J. (1996). MR cranial image segmentation - a morphological and clustering approach. 184-189. Paper presented at Proceedings of the 1996 IEEE Southwest Symposium on Image Analysis and Interpretation, San Antonio, TX, USA, .