Image Analysis Techniques for Automated IVUS Contour Detection

Maria Papadogiorgaki, Vasileios Mezaris, Yiannis S. Chatzizisis, George D. Giannoglou, Ioannis Kompatsiaris

Research output: Contribution to journalArticlepeer-review

67 Scopus citations


Intravascular ultrasound (IVUS) constitutes a valuable technique for the diagnosis of coronary atherosclerosis. The detection of lumen and media-adventitia borders in IVUS images represents a necessary step towards the reliable quantitative assessment of atherosclerosis. In this work, a fully automated technique for the detection of lumen and media-adventitia borders in IVUS images is presented. This comprises two different steps for contour initialization: one for each corresponding contour of interest and a procedure for the refinement of the detected contours. Intensity information, as well as the result of texture analysis, generated by means of a multilevel discrete wavelet frames decomposition, are used in two different techniques for contour initialization. For subsequently producing smooth contours, three techniques based on low-pass filtering and radial basis functions are introduced. The different combinations of the proposed methods are experimentally evaluated in large datasets of IVUS images derived from human coronary arteries. It is demonstrated that our proposed segmentation approaches can quickly and reliably perform automated segmentation of IVUS images. (E-mail:

Original languageEnglish (US)
Pages (from-to)1482-1498
Number of pages17
JournalUltrasound in Medicine and Biology
Issue number9
StatePublished - Sep 2008
Externally publishedYes


  • Contour detection
  • Intravascular ultrasound
  • Radial basis functions
  • Segmentation

ASJC Scopus subject areas

  • Biophysics
  • Radiological and Ultrasound Technology
  • Acoustics and Ultrasonics


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