A thinning algorithm to extract medial lines from 3D medical images

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

5 Citations (Scopus)

Abstract

This paper presents an efficient parallel algorithm for thinning elongated 3D binary objects (e.g., bony structures, vessel trees, or airway trees). This algorithm directly extracts medial lines (i.e., without creating medial surface). One iteration step consists of 12 subiterations (instead of 6, which is the usual case) according to the selected 12 deletion directions. Our topology preserving algorithm gives satisfactory results for synthetic data tests and for MR angiography brain studies.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages411-416
Number of pages6
Volume1230
ISBN (Print)3540630465, 9783540630463
Publication statusPublished - 1997
Event15th International Conference on Information Processing in Medical Imaging, IPMI 1997 - Poultney, United States
Duration: Jun 9 1997Jun 13 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1230
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other15th International Conference on Information Processing in Medical Imaging, IPMI 1997
CountryUnited States
CityPoultney
Period6/9/976/13/97

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ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Palágyi, K., & Kuba, A. (1997). A thinning algorithm to extract medial lines from 3D medical images. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1230, pp. 411-416). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1230). Springer Verlag.