Segmentation of three-dimensional intravascular ultrasound images using spectral analysis and a dual active surface model

Intravascular ultrasound (IVUS) imaging provides detailed assessment of the coronary anatomy and can be used as at quantitative tool for tracking the progression of atherosclerotic disease. The geometric information also provides evaluation of positive remodeling, a phenomenon linked to the likelihood of plaque rupture. To provide this valuable information, luminal and medial-adventitial borders must be identified in the sequence of IVUS images, a problem traditionally approached using gray-scale intensity based algorithms. However, by acquiring the radiofrequency (RF) IVUS data, the frequency information that is typically ignored can be used to improve segmentation algorithms.