Topological active volumes for segmentation and reconstruction using 3D-edge detectors

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents a new methodology for automatic 3D segmentation and shape reconstruction of bones from tomographic cross-sections. This methodology uses 3D edge detectors and the Topological Active Volumes (TAV) model. TAV model is based on deformable models, it is able to integrate the most representative characteristics of the region-based and boundary-based segmentation models and it also provides information about the topological properties of the inside of detected objects. This model has the ability to perform topological local changes in its structure during the adjustment phase in order to: obtain a specific adjustment to object's local singularities, find several objects in the scene and identify and delimit holes in detected structures.

Original languageEnglish
Title of host publicationProceedings of the Fourth IASTED International Conference on Visualization, Imaging, and Image Processing
EditorsJ.J. Villanueva
Pages441-446
Number of pages6
Publication statusPublished - 2004
Externally publishedYes
EventProceedings of the Fourth IASTED International Conference on Visualization, Imaging, and Image Processing - Marbella, Spain
Duration: 6 Sept 20048 Sept 2004

Publication series

NameProceedings of the Fourth IASTED International Conference on Visualization, Imaging, and Image Processing

Conference

ConferenceProceedings of the Fourth IASTED International Conference on Visualization, Imaging, and Image Processing
Country/TerritorySpain
CityMarbella
Period6/09/048/09/04

Keywords

  • 3D edge detectors
  • 3D object extraction
  • Active nets
  • Active volumes
  • Medical image segmentation
  • Surface reconstruction

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