Title :
Tissue characterization in intravascular ultrasound images
Author :
Zhang, Xiangmin ; McKay, Charles R. ; Sonka, Milan
Author_Institution :
Dept. of Electr. & Comput. Eng., Iowa Univ., Iowa City, IA, USA
Abstract :
Intravascular ultrasound (IVUS) imaging permits direct visualization of vascular pathology. It has been used to evaluate lumen and plaque in coronary arteries and its clinical significance for guidance of coronary interventions is increasingly recognized. Conventional manual evaluation is tedious and time consuming. This paper describes a highly automated approach to segmentation of coronary wall and plaque, and determination of plaque composition in individual IVUS images and pullback image sequences. The determined regions of plaque were classified in one of three classes: soft plaque, hard plaque, or hard plaque shadow. The method´s performance was assessed in vitro and in vivo in comparison with observer-defined independent standards. In the analyzed images and image sequences, the mean border positioning error of the wall and plaque borders ranged from 0.13-0.17 mm. Plaque classification correctness was 90%,.
Keywords :
angiocardiography; biomedical ultrasonics; image segmentation; image sequences; medical image processing; border positioning error; coronary interventions guidance; coronary wall; direct visualization; hard plaque; intravascular ultrasound images; lumen; medical diagnostic imaging; observer-defined independent standards; plaque classification correctness; plaque composition determination; pullback image sequences; soft plaque; tissue characterization; vascular pathology; Arteries; Image analysis; Image segmentation; Image sequence analysis; Image sequences; In vitro; In vivo; Pathology; Ultrasonic imaging; Visualization; Algorithms; Cadaver; Coronary Artery Disease; Coronary Vessels; Humans; Ultrasonography;
Journal_Title :
Medical Imaging, IEEE Transactions on