skip to main content
Show Results with:

3D medical image segmentation technique

El–said, Shaimaa Ahmed

International journal of biomedical engineering and technology. Volume 17:Number 3 (2015); pp 232-251 -- Inderscience Enterprises Ltd

Online access

  • Title:
    3D medical image segmentation technique
  • Author: El–said, Shaimaa Ahmed
  • Found In: International journal of biomedical engineering and technology. Volume 17:Number 3 (2015); pp 232-251
  • Journal Title: International journal of biomedical engineering and technology
  • Subjects: Biomedical engineering--Periodicals; 3D image segmentation--medical imaging--abnormalities--MRI--magnetic resonance imaging--contour filling--graph cut; Dewey: 610.28
  • Rights: legaldeposit
  • Publication Details: Inderscience Enterprises Ltd
  • Abstract:

    Despite continuing advances in mathematical models for automatic segmentation, many medical practitioners still rely on 2D manual delineation, due to the lack of intuitive automatic tools in 3D. In this paper, an efficient 3D medical image segmentation technique is proposed to provide 3D representation of the segmented regions. It uses graph cut and contour filling algorithms. It uses the normalised cut method with the eigenvector of the second smallest eigenvalue to solve the image segmentation problem, and the contour filling algorithm to ensure that the segmented region is free of gap and hole artefacts. The experimental results reveal that the proposed technique can provide a 3D representation of the region of interest successfully. The segmentations produced by this method are more realistic than the previously proposed segmentation techniques besides its effectiveness in reducing the amount of gaps and holes.


  • Identifier: System Number: LDEAvdc_100068227845.0x000001; Journal ISSN: 1752-6418
  • Publication Date: 2015
  • Physical Description: Electronic
  • Shelfmark(s): ELD Digital store

Searching Remote Databases, Please Wait