Automated 3D vascular segmentation in CT hepatic venography

Catalin Fetita, Olivier Lucidarme, Françoise Prêteux

Research output: Contribution to journalConference articlepeer-review

Abstract

In the framework of preoperative evaluation of the hepatic venous anatomy in living-donor liver transplantation or oncologic rejections, this paper proposes an automated approach for the 3D segmentation of the liver vascular structure from 3D CT hepatic venography data. The developed segmentation approach takes into account the specificities of anatomical structures in terms of spatial location, connectivity and morphometric properties. It implements basic and advanced morphological operators (closing, geodesic dilation, gray-level reconstruction, sup-constrained connection cost) in mono- and multi-resolution filtering schemes in order to achieve an automated 3D reconstruction of the opacified hepatic vessels. A thorough investigation of the venous anatomy including morphometric parameter estimation is then possible via computer-vision 3D rendering, interaction and navigation capabilities.

Original languageEnglish
Article number59160B
Pages (from-to)1-12
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume5916
DOIs
Publication statusPublished - 1 Dec 2005
Externally publishedYes
EventMathematical Methods in Pattern and Image Analysis - San Diego, CA, United States
Duration: 3 Aug 20054 Aug 2005

Keywords

  • 3D mathematical morphology
  • 3D vascular segmentation
  • CT hepatic venography
  • Graylevel reconstruction
  • Sup-constrained connection cost
  • Surgical planning

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