Intravascular ultrasound (IVUS) is a widely used interventional imaging technique for the assessment of atherosclerosis plaque. Due to pulsatile heart motions, transverse and longitudinal motions are observed during in vivo pullbacks of IVUS sequences. These motion artifacts can mislead the volume-based data retrieved from IVUS studies and hinder the visualization of the vessel condition. To overcome this problem, a new fully automatic image-based gating algorithm was proposed in the current study. We utilized the phase information of the dual-tree complex wavelet transform (DT-CWT) coefficients to detect the motion of edge-like structures. For each IVUS sequence, first, six motion signals were detected by analyzing the phase of DT-CWT coefficients in six different directions. Then, the three best motion signals were selected by analyzing the frequency properties of each signal. Subsequently, these extracted signals were filtered using a modified Butterworth band-pass filter and the gated sequence was formed by using a combination of them. The proposed method was compared to four state-of-the-art methods and its frequency spectrum had more accurate characteristics in the cardiac frequency. In addition, the gated sequence extracted by the proposed method had the highest similarity to the extracted gated sequence by the physician.

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http://dx.doi.org/10.1109/TMI.2019.2914074DOI Listing

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