A probabilistic level set formulation for interactive organ segmentation

Daniel Cremers, Oliver Fluck, Mikael Rousson, Shmuel Aharon

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

36 Scopus citations


Level set methods have become increasingly popular as a framework for image segmentation. Yet when used as a generic segmentation tool, they suffer from an important drawback: Current formulations do not allow much user interaction. Upon initialization, boundaries propagate to the final segmentation without the user being able to guide or correct the segmentation. In the present work, we address this limitation by proposing a probabilistic framework for image segmentation which integrates input intensity information and user interaction on equal footings. The resulting algorithm determines the most likely segmentation given the input image and the user input. In order to allow a user interaction in real-time during the segmentation, the algorithm is implemented on a graphics card and in a narrow band formulation.

Original languageEnglish
Title of host publicationMedical Imaging 2007
Subtitle of host publicationImage Processing
EditionPART 1
StatePublished - 2007
Externally publishedYes
EventMedical Imaging 2007: Image Processing - San Diego, CA, United States
Duration: 18 Feb 200720 Feb 2007

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
NumberPART 1
ISSN (Print)1605-7422


ConferenceMedical Imaging 2007: Image Processing
Country/TerritoryUnited States
CitySan Diego, CA


  • CT
  • Graphics processor unit (GPU)
  • Interactive
  • Level set
  • MR
  • Medical imaging
  • Probabilistic
  • Segmentation
  • Ultrasound
  • User interaction


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