Medical image segmentation using multi-level set partitioning with topological graph prior

Saif Dawood Salman Al-Shaikhli, Michael Ying Yang, Bodo Rosenhahn

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

7 Citations (Scopus)

Abstract

In this paper, we propose an approach for multi-region segmentation based on a topological graph prior within a multi-level set (MLS) formulation. We consider topological graph prior information to evolve the contour based on a topological relationship presented via a graph relation. This novel method is capable of segmenting adjacent objects with very close gray level that would be difficult to segment correctly using standard methods. We describe our algorithm and show the graph prior technique to explain how it gives precise multi-region segmentation. We validate our algorithm with numerous abdominal and brain image databases and compare it to other multi-region segmentation methods to demonstrate its accuracy and computational efficiency.

Original languageEnglish
Title of host publicationImage and Video Technology – PSIVT 2013 Workshops
Subtitle of host publicationGCCV 2013, GPID 2013, PAESNPR 2013, and QACIVA 2013, Guanajuato, Mexico, October 28-29, 2013, Revised Selected Papers
EditorsFay Huang, Akihiro Sugimoto
Place of PublicationBerlin, Heidelberg
PublisherSpringer
Pages157-168
Number of pages12
ISBN (Electronic)978-3-642-53926-8
ISBN (Print)978-3-642-53925-1
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes
Event6th Pacific-Rim Symposium on Image and Video Technology 2013 - Guanajuato, Mexico
Duration: 28 Oct 20131 Nov 2013
Conference number: 6
http://www.psivt.org/psivt2013/

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume8334
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th Pacific-Rim Symposium on Image and Video Technology 2013
Abbreviated titlePSIVT 2013
CountryMexico
CityGuanajuato
Period28/10/131/11/13
Internet address

Keywords

  • Level set
  • Medical image
  • Multi-region
  • Segmentation
  • Topological graph

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