A three-level graph based interactive volume segmentation system

Runzhen Huang, Kwan-Liu Ma

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

We present a new hierarchical graph representation for volume data as well as its associated operations to enable interactive feature segmentation for high-resolution volume data. Our method constructs a low-resolution graph which represents a coarser resolution of the data. This graph enables the user to interactively sample and edit a feature of interest by drawing strokes on data slices. A subgraph representing the feature is derived with a growing process, and is used to extract the high-resolution version of the feature from the original volume data by performing an automatic mapping and refinement procedure. Our three-level, graph-based approach overcomes partial volume effects that are introduced by downsampling the volume data, and enables interactive segmentation of fine features. We demonstrate the effectiveness of this approach with several challenging 3D segmentation applications.

Original languageEnglish (US)
Title of host publicationAdvances in Visual Computing - First International Symposium, ISVC 2005, Proceedings
Pages143-150
Number of pages8
StatePublished - Dec 1 2005
EventFirst International Symposium on Advances in Visual Computing, ISVC 2005 - Lake Tahoe, NV, United States
Duration: Dec 5 2005 → Dec 7 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3804 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

OtherFirst International Symposium on Advances in Visual Computing, ISVC 2005
CountryUnited States
CityLake Tahoe, NV
Period12/5/05 → 12/7/05

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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    Huang, R., & Ma, K-L. (2005). A three-level graph based interactive volume segmentation system. In Advances in Visual Computing - First International Symposium, ISVC 2005, Proceedings (pp. 143-150). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3804 LNCS).