A State-of-the-Art Review on Segmentation Algorithms in Intravascular Ultrasound (IVUS) Images

Amin Katouzian, Elsa D Angelini, Stephane Carlier

Onderzoeksoutput: Articlepeer review

120 Citaten (Scopus)


Over the past two decades, intravascular ultrasound (IVUS) image segmentation has remained a challenge for researchers while the use of this imaging modality is rapidly growing in catheterization procedures and in research studies. IVUS provides cross-sectional grayscale images of the arterial wall and the extent of atherosclerotic plaques with high spatial resolution in real time. In this paper, we review recently developed image processing methods for the detection of media-adventitia and luminal borders in IVUS images acquired with different transducers operating at frequencies ranging from 20 to 45 MHz. We discuss methodological challenges, lack of diversity in reported datasets, and weaknesses of quantification metrics that make IVUS segmentation still an open problem despite all efforts. In conclusion, we call for a common reference database, validation metrics, and ground-truth definition with which new and existing algorithms could be benchmarked.
Originele taal-2English
Pagina's (van-tot)823-834
Aantal pagina's12
TijdschriftIEEE Transactions on Information Technology in BioMedicine
Nummer van het tijdschrift5 SI
StatusPublished - sep 2012


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