A novel active contour model for fully automated segmentation of intravascular ultrasound images: in vivo validation in human coronary arteries.
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.
Giannoglou
George D
GD
Cardiovascular Engineering and Atherosclerosis Laboratory, 1st Cardiology Department, AHEPA University Hospital, Aristotle University Medical School, Thessaloniki, Greece. yan@med.auth.gr
Chatzizisis
Yiannis S
YS
Koutkias
Vassilis
V
Kompatsiaris
Ioannis
I
Papadogiorgaki
Maria
M
Mezaris
Vasileios
V
Parissi
Eirini
E
Diamantopoulos
Panagiotis
P
Strintzis
Michael G
MG
Maglaveras
Nicos
N
Parcharidis
George E
GE
Louridas
George E
GE
D000465:Algorithms; D003324:Coronary Artery Disease / Q000175:diagnosis* / Q000000981:diagnostic imaging; D003331:Coronary Vessels / Q000000981:diagnostic imaging*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016014:Linear Models; D015588:Observer Variation; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014463:Ultrasonography / Q000379:methods*