Current methods in medical image segmentation

Dzung L. Pham*, Chenyang Xu, Jerry L. Prince

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2017 Scopus citations

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

Keywords

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

Cite this