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Simultaneous Registration of Location and Orientation in Intravascular Ultrasound Pullbacks Pairs Via 3D Graph-Based Optimization

机译:通过基于3D图的优化同时注册血管内超声回撤对中的位置和方向

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摘要

A novel method is reported for simultaneous registration of location (axial direction) and orientation (circumferential direction) of two intravascular ultrasound (IVUS) pullbacks of the same vessel taken at different times. Monitoring plaque progression or regression (e.g., during lipid treatment) is of high clinical relevance. Our method uses a 3D graph optimization approach, in which the cost function jointly reflects similarity of plaque morphology and plaque/perivascular image appearance. Graph arcs incorporate prior information about temporal correspondence of the two IVUS sequences and limited angular twisting between consecutive IVUS images. Additionally, our approach automatically identifies starting and ending frame pairs in the two IVUS pullbacks. Validation of our method was performed in 29 pairs of IVUS baseline/follow-up pullback sequences consisting of 8 622 IVUS image frames in total. In comparison to manual registration by three experts, the average location and orientation registration errors ranged from 0.72 mm to 0.79 mm and from 7.3 to 9.3, respectively, all close to the inter-observer variability with no difference being statistically significant . Rotation angles determined by our automated approach and expert observers showed high correlation ( of 0.97 to 0.98) and agreed closely (mutual bias between the automated method and expert observers ranged from to 0.15). Compared with state-of-the-art approaches, the new method offers lower errors in both location and orientation regis- ration. Our method offers highly automated and accurate IVUS pullback registration and can be employed in IVUS-based studies of coronary disease progression, enabling more focal studies of coronary plaque development and transition of vulnerability.
机译:报道了一种新方法,用于同时记录同一血管在不同时间拍摄的两次血管内超声(IVUS)回撤的位置(轴向)和方向(周向)。监测斑块进展或消退(例如在脂质治疗期间)具有高度的临床意义。我们的方法使用3D图形优化方法,其中成本函数共同反映了斑块形态和斑块/血管周围图像外观的相似性。图弧结合了有关两个IVUS序列的时间对应关系的先验信息,以及连续IVUS图像之间的有限角度扭曲。此外,我们的方法会自动识别两个IVUS回调中的开始和结束帧对。我们的方法的验证是在29对IVUS基线/随访拉回序列中进行的,这些序列总共包含8 622个IVUS图像帧。与三位专家的手动配准相比,平均位置和方向配准误差分别在0.72 mm至0.79 mm和7.3至9.3范围内,均接近观察者间的差异,差异无统计学意义。由我们的自动方法和专家观察者确定的旋转角度显示出很高的相关性(从0.97到0.98)并且一致(自动方法和专家观察者之间的相互偏差介于-0.15之间)。与最先进的方法相比,新方法在位置和方向注册中的误差较小。我们的方法提供了高度自动化和准确的IVUS撤回注册,可用于基于IVUS的冠状动脉疾病进展研究中,从而能够更集中地研究冠状动脉斑块发展和脆弱性转变。

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