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Related Experiment Video

Updated: Mar 12, 2026

A Magnetic Resonance Imaging-based Computational Protocol for Analysis of Plaque Morphology and Hemodynamics in Patients with Carotid Artery Stenosis
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Automatic Algorithm for Segmentation of Atherosclerotic Carotid Plaque.

Lilla Bonanno1, Fabrizio Sottile2, Rosella Ciurleo1

  • 1IRCCS Centro Neurolesi "Bonino-Pulejo," Messina, Italy.

Journal of Stroke and Cerebrovascular Diseases : the Official Journal of National Stroke Association
|November 4, 2016
PubMed
Summary

This study presents an automatic method using image segmentation to identify and measure carotid plaques, aiding in stroke risk assessment. The system accurately characterizes atherosclerotic carotid plaques.

Keywords:
Automatic segmentationcarotid atherosclerosissnake algorithmultrasound image

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Area of Science:

  • Medical Imaging
  • Cardiovascular Research
  • Stroke Prevention

Background:

  • Carotid atherosclerosis is a primary cause of stroke.
  • Intima-media thickness, plaque identification, and stenosis classification are key assessment parameters.
  • Understanding carotid atherosclerosis aids in stroke risk stratification.

Purpose of the Study:

  • To develop an automatic method for carotid plaque segmentation.
  • To improve the comprehension and assessment of carotid atherosclerosis.
  • To enhance the identification and characterization of atherosclerotic plaques.

Main Methods:

  • Applied the snake algorithm for image segmentation.
  • Studied 44 subjects (22 with and 22 without carotid plaques).
  • Utilized image analysis to segment carotid plaques.

Main Results:

  • Achieved 82% diagnostic accuracy for plaque identification.
  • Demonstrated high interclass correlation coefficients for plaque parameters (echogenicity, perimeter, area).
  • Reported sensitivity of 79% and specificity of 85% with a cutoff of 224.5.

Conclusions:

  • An automatic image segmentation system can effectively identify carotid plaques.
  • The developed method aids in characterizing and measuring atherosclerotic carotid plaques.
  • This technology supports better assessment of atherosclerosis and stroke risk.