Automated image segmentation: Issues and applications

Alain Pitiot, Hervé Delingette, Paul M. Thompson

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

5 Scopus citations

Abstract

The explosive growth in medical imaging technologies has been matched by a tremendous increase in the number of investigations centered on the structural and functional organization of the human body. A pivotal first step towards elucidating the correlation between structure and function, accurate and robust segmentation is a major objective of computerized medicine. It is also a substantial challenge in view of the wide variety of shapes and appearances that organs, anatomical structures and tissues can exhibit in medical images. This chapter surveys the actively expanding field of medical image segmentation. We discuss the main issues that pertain to the remarkably diverse range of proposed techniques. Among others, the characteristics of a suitable segmentation paradigm, the introduction of a priori knowledge, robustness and validation are detailed and illustrated with relevant techniques and applications.

Original languageEnglish
Title of host publicationMedical Imaging Systems Technology
Subtitle of host publicationVolume 3: Methods in General Anatomy
PublisherWorld Scientific Publishing Co.
Pages195-244
Number of pages50
ISBN (Electronic)9789812701060
ISBN (Print)9812563644, 9789812569912
DOIs
StatePublished - 1 Jan 2005
Externally publishedYes

Keywords

  • A priori knowledge
  • Medical imaging
  • Review
  • Robustness
  • Segmentation
  • Segmentation paradigm
  • Validation

Fingerprint

Dive into the research topics of 'Automated image segmentation: Issues and applications'. Together they form a unique fingerprint.

Cite this