Numerical experiments for segmenting medical images using level sets

A. Araújo, D. M.G. Comissiong, G. Stadler

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

Abstract

Image segmentation is the process by which objects are separated from background information. Structural segmentation from 2D and 3D images is an important step in the analysis of medical image data. In this work, we utilize level set algorithms and active contours without edges to segment two and three-dimensional image data. Besides synthetical data, we also use magnetic resonance images of the human brain provided by the Institute of Biomedical Research in Light and Images of the University of Coimbra (IBILI).

Original languageEnglish (US)
Title of host publicationProceedings of VIPIMAGE 2007 - 1st ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing
Pages91-96
Number of pages6
StatePublished - 2008
EventVIPIMAGE 2007 - 1st ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing - Porto, Portugal
Duration: Oct 17 2007Oct 19 2007

Publication series

NameProceedings of VIPIMAGE 2007 - 1st ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing

Other

OtherVIPIMAGE 2007 - 1st ECCOMAS Thematic Conference on Computational Vision and Medical Image Processing
CountryPortugal
CityPorto
Period10/17/0710/19/07

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Biomedical Engineering

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