Current methods in medical image segmentation

Annu Rev Biomed Eng. 2000;2:315-37. doi: 10.1146/annurev.bioeng.2.1.315.


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.

Publication types

  • Review

MeSH terms

  • Algorithms
  • Biomedical Engineering
  • Brain / anatomy & histology
  • Cluster Analysis
  • Computer Simulation
  • Female
  • Heart / anatomy & histology
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Image Processing, Computer-Assisted / statistics & numerical data
  • Magnetic Resonance Imaging
  • Mammography
  • Markov Chains
  • Models, Anatomic
  • Neural Networks, Computer