Automatic segmentation of brain images. Selection of region extraction methods

Leiguang Gong, Casimir A. Kulikowski, Reuben S. Mezrich

Research output: Contribution to journalConference articlepeer-review

8 Scopus citations

Abstract

This paper describes specifically a local-binary thresholding method and a new global-multiple thresholding technique developed for MR image segmentation and analysis. The initial testing results on their segmentation performance are presented, followed by a comparative analysis of the two methods and their ability to extract different types of normal and abnormal brain structures - the brain matter itself, tumors, regions of edema surrounding lesions, Multiple Sclerosis lesions, and the ventricles of the brain. The analysis and experimental results show that the global multiple thresholding techniques are more than adequate for extracting regions that correspond to the major brain structures, while local binary thresholding is helpful for more accurate delineation of small lesions such as those produced by MS, and for the precise refinement of lesion boundaries.

Original languageEnglish (US)
Pages (from-to)144-153
Number of pages10
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume1450
StatePublished - 1991
EventBiomedical Image Processing II - San Jose, CA, USA
Duration: Feb 25 1991Feb 27 1991

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Automatic segmentation of brain images. Selection of region extraction methods'. Together they form a unique fingerprint.

Cite this