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A coronary artery segmentation method based on multiscale analysis and region growing.

Asma Kerkeni1, Asma Benabdallah1, Antoine Manzanera2

  • 1Laboratoire Technologie et Imagerie Médicale, Faculté de Médecine, Université de Monastir, Tunisia.

Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society
|January 10, 2016
PubMed
Summary

A new multiscale region growing (MSRG) method accurately segments coronary arteries in X-ray angiograms. This approach improves detection of thin vessels and maintains performance in challenging conditions like noise and stenosis.

Keywords:
Coronary arteryDirectionHessianMultiscaleRegion growingSegmentationVesselness

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Area of Science:

  • Medical Imaging
  • Cardiovascular Diagnostics
  • Image Segmentation

Background:

  • Accurate coronary artery segmentation is crucial for diagnosing conditions like stenosis and assessing cardiac function.
  • Existing segmentation methods often struggle with thin vessels, noise, and poor contrast in X-ray angiograms.

Purpose of the Study:

  • To develop and evaluate a novel multiscale region growing (MSRG) method for improved coronary artery segmentation in 2D X-ray angiograms.

Main Methods:

  • A region growing rule integrating vesselness and direction information was introduced.
  • An iterative, multiscale search strategy was employed, using selected points as seeds for subsequent steps.
  • The method was tested with various enhancement filters, notably the Frangi filter.

Main Results:

  • The MSRG method achieved segmentation of approximately 80% in easier cases and 70% in challenging cases, with a mean precision of 82%.
  • It demonstrated superior sensitivity compared to other segmentation methods.
  • The Frangi filter integration yielded optimal results.

Conclusions:

  • The proposed MSRG method provides robust and accurate coronary artery segmentation, even in the presence of noise, stenosis, and poor contrast.
  • Its multiscale approach effectively captures fine and peripheral vessels, outperforming existing techniques.