Fully automated carotid plaque segmentation in combined contrast-enhanced and B-mode ultrasound

Zeynettin Akkus, Diego D.B. Carvalho, Stijn C.H. van den Oord, Arend F.L. Schinkel, Wiro J. Niessen, Nico de Jong, Antonius F.W. van der Steen, Stefan Klein, Johan G. Bosch

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


Carotid plaque segmentation in B-mode ultrasound (BMUS) and contrast-enhanced ultrasound (CEUS) is crucial to the assessment of plaque morphology and composition, which are linked to plaque vulnerability. Segmentation in BMUS is challenging because of noise, artifacts and echo-lucent plaques. CEUS allows better delineation of the lumen but contains artifacts and lacks tissue information. We describe a method that exploits the combined information from simultaneously acquired BMUS and CEUS images. Our method consists of non-rigid motion estimation, vessel detection, lumen-intima segmentation and media-adventitia segmentation. The evaluation was performed in training (n=20 carotids) and test (n=28) data sets by comparison with manually obtained ground truth. The average root-mean-square errors in the training and test data sets were comparable for media-adventitia (411±224 and 393±239μm) and for lumen-intima (362±192 and 388±200μm), and were comparable to inter-observer variability. To the best of our knowledge, this is the first method to perform fully automatic carotid plaque segmentation using combined BMUS and CEUS.

Original languageEnglish (US)
Pages (from-to)517-531
Number of pages15
JournalUltrasound in Medicine and Biology
Issue number2
StatePublished - 2015


  • B-Mode
  • Carotid plaques
  • Contrast-enhanced ultrasound
  • Lumen-intima segmentation
  • Media-adventitia segmentation
  • Plaque segmentation
  • Vessel detection

ASJC Scopus subject areas

  • Biophysics
  • Radiological and Ultrasound Technology
  • Acoustics and Ultrasonics


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