Automated connectivity-based thresholding segmentation of midsagittal brain MR images

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

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

1 Citation (Scopus)

Abstract

In this paper, we propose an algorithm for automated segmentation of midsagittal brain MR images. First, we apply thresholding to obtain binary images. From the binary images, we locate some landmarks. Based on the landmarks and anatomical information, we preprocess the binary images to eliminate small regions and remove the skull, which substantially simplifies the subsequent operations. We perform segmentation in the binary image as much as possible and then return to the gray scale image to solve problematic areas. We propose a new connectivity-based thresholding segmentation to separate brain regions from surrounding tissues. Experiments show promising results.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
Pages713-724
Number of pages12
Volume2727
Edition2/-
Publication statusPublished - 1996 Dec 1
EventVisual Communications and Image Processing'96. Part 2 (of 3) - Orlando, FL, USA
Duration: 1996 Mar 171996 Mar 20

Other

OtherVisual Communications and Image Processing'96. Part 2 (of 3)
CityOrlando, FL, USA
Period96/3/1796/3/20

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

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  • Cite this

    Lee, C., Unser, M. A., & Ketter, T. A. (1996). Automated connectivity-based thresholding segmentation of midsagittal brain MR images. In Proceedings of SPIE - The International Society for Optical Engineering (2/- ed., Vol. 2727 , pp. 713-724)