Segmentation of the common carotid artery walls based on a frequency implementation of active contours: segmentation of the common carotid artery walls

J Digit Imaging. 2013 Feb;26(1):129-39. doi: 10.1007/s10278-012-9481-7.

Abstract

Atherosclerosis is one of the most extended cardiovascular diseases nowadays. Although it may be unnoticed during years, it also may suddenly trigger severe illnesses such as stroke, embolisms or ischemia. Therefore, an early detection of atherosclerosis can prevent adult population from suffering more serious pathologies. The intima-media thickness (IMT) of the common carotid artery (CCA) has been used as an early and reliable indicator of atherosclerosis for years. The IMT is manually computed from ultrasound images, a process that can be repeated as many times as necessary (over different ultrasound images of the same patient), but also prone to errors. With the aim to reduce the inter-observer variability and the subjectivity of the measurement, a fully automatic computer-based method based on ultrasound image processing and a frequency-domain implementation of active contours is proposed. The images used in this work were obtained with the same ultrasound scanner (Philips iU22 Ultrasound System) but with different spatial resolutions. The proposed solution does not extract only the IMT but also the CCA diameter, which is not as relevant as the IMT to predict future atherosclerosis evolution but it is a statistically interesting piece of information for the doctors to determine the cardiovascular risk. The results of the proposed method have been validated by doctors, and these results are visually and numerically satisfactory when considering the medical measurements as ground truth, with a maximum deviation of only 3.4 pixels (0.0248 mm) for IMT.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Atherosclerosis / diagnostic imaging*
  • Carotid Artery, Common / diagnostic imaging*
  • Carotid Intima-Media Thickness*
  • Humans
  • Image Interpretation, Computer-Assisted / methods*