Accuracy in Prediction of Catheter Rotation in IVUS With Feature-Based Optical Flow—A Phantom Study

The quantitative assessment of and compensation for catheter rotation in intravascular ultrasound images presents a fundamental problem for noninvasive characterization of the mechanical properties of the coronary arteries. A method based on the scale-space optical flow algorithm with a feature-based weighting scheme is proposed to account for the aforementioned artifact. The computed vector field, describing the misalignment between two consecutive frames, allows the quantitative assessment of the amount of vessel wall tissue motion, which is directly related to the catheter rotation. Algorithm accuracy and robustness were demonstrated on two tissue-mimicking phantoms, subjected to controlled amount of angular deviation. The proposed method shows a great reliability in the prediction of catheter rotational motion up to 4deg.