An abdominal aortic aneurysm segmentation method: Level set with region and statistical information

Feng Zhuge, Geoffrey D. Rubin, Shaohua Sun, Sandy Napel

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

We present a system for segmenting the human aortic aneurysm in CT angiograms (CTA), which, in turn, allows measurements of volume and morphological aspects useful for treatment planning. The system estimates a rough "initial surface," and then refines it using a level set segmentation scheme augmented with two external analyzers: The global region analyzer, which incorporates a priori knowledge of the intensity, volume, and shape of the aorta and other structures, and the local feature analyzer, which uses voxel location, intensity, and texture features to train and drive a support vector machine classifier. Each analyzer outputs a value that corresponds to the likelihood that a given voxel is part of the aneurysm, which is used during level set iteration to control the evolution of the surface. We tested our system using a database of 20 CTA scans of patients with aortic aneurysms. The mean and worst case values of volume overlap, volume error, mean distance error, and maximum distance error relative to human tracing were 95.3%±1.4% (s.d.); worst case=92.9%, 3.5%±2.5% (s.d.); worst case=7.0%, 0.6±0.2 mm (s.d.); worst case=1.0 mm, and 5.2±2.3mm (s.d.); worstcase=9.6 mm, respectively. When implemented on a 2.8 GHz Pentium IV personal computer, the mean time required for segmentation was 7.4±3.6min (s.d.). We also performed experiments that suggest that our method is insensitive to parameter changes within 10% of their experimentally determined values. This preliminary study proves feasibility for an accurate, precise, and robust system for segmentation of the abdominal aneurysm from CTA data, and may be of benefit to patients with aortic aneurysms.

Original languageEnglish (US)
Pages (from-to)1440-1453
Number of pages14
JournalMedical physics
Volume33
Issue number5
DOIs
StatePublished - 2006
Externally publishedYes

Keywords

  • Abdominal aortic aneurysm
  • CT angiography
  • Deformable model

ASJC Scopus subject areas

  • Biophysics
  • Radiology Nuclear Medicine and imaging

Fingerprint

Dive into the research topics of 'An abdominal aortic aneurysm segmentation method: Level set with region and statistical information'. Together they form a unique fingerprint.

Cite this