Medical image segmentation for virtual endoscopy

László Szilágyi, Zoltán Benyó, Sándor M. Szilágyi

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

1 Citation (Scopus)


This paper presents new concepts in the design and implementation of a virtual endoscope. Starting from standard magnetic resonance images, and applying a two-step image processing, inner views of the human body can be obtained, even of such parts of the body, which cannot be penetrated by a traditional endoscope. The first step of the image processing consists in an enhanced version of the fuzzy C-means segmentation. Then a shape recovery algorithm is employed in order to reconstruct the 3-D object. The algorithms provide good-quality segmented images a very quick way, which makes them excellent tools to support a virtual endoscopy.

Original languageEnglish
Title of host publicationProceedings of the 16th IFAC World Congress, IFAC 2005
PublisherIFAC Secretariat
Number of pages5
ISBN (Print)008045108X, 9780080451084
Publication statusPublished - Jan 1 2005

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
ISSN (Print)1474-6670


  • Computer tomography
  • Fuzzy logic
  • Image reconstruction
  • Image segmentation
  • Medical applications

ASJC Scopus subject areas

  • Control and Systems Engineering

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  • Cite this

    Szilágyi, L., Benyó, Z., & Szilágyi, S. M. (2005). Medical image segmentation for virtual endoscopy. In Proceedings of the 16th IFAC World Congress, IFAC 2005 (pp. 243-247). (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 16). IFAC Secretariat.