A novel active contour model for fully automated segmentation of intravascular ultrasound images: In vivo validation in human coronary arteries

  • Authors:

  • George D. Giannoglou;Yiannis S. Chatzizisis;Vassilis Koutkias;Ioannis Kompatsiaris;Maria Papadogiorgaki;Vasileios Mezaris;Eirini Parissi;Panagiotis Diamantopoulos;Michael G. Strintzis;Nicos Maglaveras;George E. Parcharidis;George E. Louridas

  • Affiliations:

  • Cardiovascular Engineering and Atherosclerosis Laboratory, 1st Cardiology Department, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece;Cardiovascular Engineering and Atherosclerosis Laboratory, 1st Cardiology Department, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece;Laboratory of Medical Informatics, Aristotle University Medical School, Thessaloniki, Greece;Informatics and Telematics Institute, Center for Research and Technology-Hellas, Thessaloniki, Greece;Informatics and Telematics Institute, Center for Research and Technology-Hellas, Thessaloniki, Greece;Informatics and Telematics Institute, Center for Research and Technology-Hellas, Thessaloniki, Greece;Informatics and Telematics Institute, Center for Research and Technology-Hellas, Thessaloniki, Greece;Department of Engineering and Design, University of Sussex, Sussex, UK;Informatics and Telematics Institute, Center for Research and Technology-Hellas, Thessaloniki, Greece;Laboratory of Medical Informatics, Aristotle University Medical School, Thessaloniki, Greece;Cardiovascular Engineering and Atherosclerosis Laboratory, 1st Cardiology Department, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece;Cardiovascular Engineering and Atherosclerosis Laboratory, 1st Cardiology Department, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece

  • Venue:
  • Computers in Biology and Medicine
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

Abstract

The detection of lumen and media-adventitia borders in intravascular ultrasound (IVUS) images constitutes a necessary step for the quantitative assessment of atherosclerotic lesions. To date, most of the segmentation methods reported are either manual, or semi-automated, requiring user interaction at some extent, which increases the analysis time and detection errors. In this work, a fully automated approach for lumen and media-adventitia border detection is presented based on an active contour model, the initialization of which is performed via an analysis mechanism that takes advantage of the inherent morphologic characteristics of IVUS images. The in vivo validation of the proposed model in human coronary arteries revealed that it is a feasible approach, enabling accurate and rapid segmentation of multiple IVUS images.