Fast retrieval of calcification from sequential intravascular ultrasound gray-scale images.

Abstract

Intravascular ultrasound (IVUS)-based tissue characterization is invaluable for the computer-aided diagnosis and interventional treatment of cardiac vessel diseases. Although the analysis of raw backscattered signals allows more accurate plaque characterization than gray-scale images, its applications are limited due to its nature of electrocardiogram-gated acquisition. Images acquired by IVUS devices that do not allow the acquisition of raw signals cannot be characterized. To address these limitations, we developed a method for fast frame-by-frame retrieval and location of calcification according to the jump features of radial gray-level variation curves from sequential IVUS gray-scale images. The proposed method consists of three main steps: (1) radial gray-level variation curves are extracted from each filtered polar view, (2) sequential images are preliminarily queried according to the maximal slopes of radial gray-level variation curves, and finally, (3) key frames that include calcification are selected through checking the gray-level features of successive pixel columns in the preliminary results. Experimental results with clinically acquired in vivo data sets indicate key frames that include calcification can be retrieved with the advantages of simplicity, high efficiency, and accuracy. Recognition results correlate well with manual characterization results obtained by experienced physicians and through virtual histology.