Current methods in medical image segmentation

Dzung L. Pham, Chenyang Xu, Jerry Ladd Prince

Research output: Contribution to journalArticle

Abstract

Image segmentation plays a crucial role in many medical-imaging applications, by automating or facilitating the delineation of anatomical structures and other regions of interest. We present a critical appraisal of the current status of semi-automated and automated methods for the segmentation of anatomical medical images. Terminology and important issues in image segmentation are first presented. Current segmentation approaches are then reviewed with an emphasis on the advantages and disadvantages of these methods for medical imaging applications. We conclude with a discussion on the future of image segmentation methods in biomedical research.

Original languageEnglish (US)
Pages (from-to)315-337
Number of pages23
JournalAnnual Review of Biomedical Engineering
Volume2
Issue number2000
StatePublished - 2000

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Image segmentation
Medical imaging
Diagnostic Imaging
Terminology
Biomedical Research

Keywords

  • Classification
  • Deformable models
  • Image processing
  • Magnetic resonance imaging
  • Medical imaging

ASJC Scopus subject areas

  • Biophysics
  • Biomedical Engineering

Cite this

Current methods in medical image segmentation. / Pham, Dzung L.; Xu, Chenyang; Prince, Jerry Ladd.

In: Annual Review of Biomedical Engineering, Vol. 2, No. 2000, 2000, p. 315-337.

Research output: Contribution to journalArticle

Pham, Dzung L. ; Xu, Chenyang ; Prince, Jerry Ladd. / Current methods in medical image segmentation. In: Annual Review of Biomedical Engineering. 2000 ; Vol. 2, No. 2000. pp. 315-337.
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