Interactive level set segmentation for image-guided therapy

Nir Ben-Zadok, Tammy Riklin-Raviv, Nahum Kiryati

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

24 Scopus citations

Abstract

Image-guided therapy procedures require the patient to remain still throughout the image acquisition, data analysis and therapy. This imposes a tight time constraint on the overall process. Automatic extraction of the pathological regions prior to the therapy can be faster than the customary manual segmentation performed by the physician. However, the image data alone is usually not sufficient for reliable and unambiguous computerized segmentation. Thus, the oversight of an experienced physician remains mandatory. We present a novel segmentation framework, that allows user feedback. A few mouse-clicks of the user, discrete in nature, are represented as a continuous energy term that is incorporated into a level-set functional. We demonstrate the proposed method on MR scans of uterine fibroids acquired prior to focused ultrasound ablation treatment. The experiments show that with a minimal user input, automatic segmentation results become practically identical to manual expert segmentation.

Original languageEnglish
Title of host publicationProceedings - 2009 IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI 2009
Pages1079-1082
Number of pages4
DOIs
StatePublished - 17 Nov 2009
Externally publishedYes
Event2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 - Boston, MA, United States
Duration: 28 Jun 20091 Jul 2009

Publication series

NameProceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

Conference

Conference2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009
Country/TerritoryUnited States
CityBoston, MA
Period28/06/091/07/09

Keywords

  • Image guided therapy
  • Level-set framework
  • MR scans segmentation
  • User interaction

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

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