Automatic recognition of corpus callosum from sagittal brain MR images

Chulhee Lee, Michael A. Unser, Terence A. Ketter

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

Abstract

We propose a new method to find the corpus callosum from sagittal brain MR images automatically. First, we calculate the statistical characteristics of the corpus callosum and obtain shape information. The recognition algorithm consists of two stages: extracting regions satisfying the statistical characteristics (gray level distributions) of the corpus callosum, and finding a region matching the shape information. An innovative feature of the algorithm is that we adaptively relax the statistical requirement until we find a region matching the shape information. In order to match the shape information, we propose a new directed window region growing algorithm instead of using conventional contour matching. Experiments show promising results.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsAndrew G. Tescher
Pages528-534
Number of pages7
Volume2564
Publication statusPublished - 1995 Dec 1
EventApplications of Digital Image Processing XVIII - San Diego, CA, USA
Duration: 1995 Jul 121995 Jul 14

Other

OtherApplications of Digital Image Processing XVIII
CitySan Diego, CA, USA
Period95/7/1295/7/14

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All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Lee, C., Unser, M. A., & Ketter, T. A. (1995). Automatic recognition of corpus callosum from sagittal brain MR images. In A. G. Tescher (Ed.), Proceedings of SPIE - The International Society for Optical Engineering (Vol. 2564, pp. 528-534)