An Alternative Approach to Spectrum-Based Atherosclerotic Plaque Characterization Techniques Using Intravascular Ultrasound (IVUS) Backscattered Signals

In this paper, the discrete wavelet packet frames are used to delineate the atherosclerotic plaque components using intravascular ultrasound (IVUS) backscattered signals. The frames are classified in an unsupervised fashion deploying K-means clustering technique and the generated prognosis histology (PH) images are quantified using relative histology images. While existing tissue characterization algorithms fail to differentiate between blood and plaque signals, the proposed algorithm can be used to estimate the lumen border at higher levels of wavelet expansion. We will demonstrate the in-vitro and invivo tissue characterization as well as lumen border detection results employing 40 MHz rotating unfocused single-element transducers. It is concluded that our two dimensional (2-D) algorithm, which is independent of the cardiac and catheter motions, performs well in both in-vivo and in-vitro cases.