Interactive segmentation based on the live wire for 3D CT chest image analysis

Kongkuo Lu, William E. Higgins

Research output: Contribution to journalArticlepeer-review

46 Scopus citations


Object: The definition of regions of interest (ROIs) such as suspect cancer nodules or lymph nodes in 3D MDCT chest images is often difficult because of the complexity of the phenomena that give rise to them. Manual slice tracing has been used commonly for such problems, but it is extremely time consuming, subject to operator biases, and does not enable reproducible results. Proposed automated 3D image-segmentation methods are generally application dependent, and even the most robust methods have difficulty in defining complex ROIs. Materials and methods: The semi-automatic interactive paradigm known as live wire has been proposed by researchers, whereby the human operator interactively defines an ROI's boundary, guided by an active automated method. We propose 2D and 3D live-wire methods that improve upon previously proposed techniques. The 2D method gives improved robustness and incorporates a search region to improve computational efficiency. The 3D method requires the operator to only consider a few 2D slices, with an automated procedure performing the bulk of the analysis. Results: For tests run with five human operators on both 2D and 3D ROIs in 3D MDCT chest images, the reproducibility was >97% and the ground-truth correspondence was at least 97%. The 2D live-wire approach was ≥14 times faster than manual slice tracing, while the 3D method was ≥28 times faster than manual slice tracing. Finally, we describe a computer-based tool and its application to 3D MDCT-based planning and follow-on live guidance of bronchoscopy. Conclusion: The live-wire methods are efficient, reliable, easy to use, and applicable to a wide range of circumstances.

Original languageEnglish (US)
Pages (from-to)151-167
Number of pages17
JournalInternational Journal of Computer Assisted Radiology and Surgery
Issue number3-4
StatePublished - 2007

All Science Journal Classification (ASJC) codes

  • Health Informatics
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Surgery
  • Biomedical Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design


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