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Automated 3D coronary sinus catheter detection using a scanning-beam digital x-ray system

机译:使用扫描束数字X射线系统自动进行3D冠状静脉窦导管检测

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Scanning-beam digital x-ray (SBDX) is an inverse geometry x-ray fluoroscopy system capable of tomosynthesis-based 3D tracking of catheter electrodes concurrent with fluoroscopic display. To facilitate respiratory motion-compensated 3D catheter tracking, an automated coronary sinus (CS) catheter detection algorithm for SBDX was developed. The technique uses the 3D localization capability of SBDX and prior knowledge of the catheter shape. Candidate groups of points representing the CS catheter are obtained from a 3D shape-constrained search. A cost function is then minimized over the groups to select the most probable CS catheter candidate. The algorithm was implemented in MATLAB and tested offline using recorded image sequences of a chest phantom containing a CS catheter, ablation catheter, and fiducial clutter. Fiducial placement was varied to create challenging detection scenarios. Table panning and elevation was used to simulate motion. The CS catheter detection method had 98.1% true positive rate and 100% true negative rate in 2755 frames of imaging. Average processing time was 12.7 ms/frame on a PC with a 3.4 GHz CPU and 8 GB memory. Motion compensation based on 3D CS catheter tracking was demonstrated in a moving chest phantom with a fixed CS catheter and an ablation catheter pulled along a fixed trajectory. The RMS error in the tracked ablation catheter trajectory was 1.41 mm, versus 10.35 mm without motion compensation. A computationally efficient method of automated 3D CS catheter detection has been developed to assist with motion-compensated 3D catheter tracking and registration of 3D cardiac models to tracked catheters.
机译:扫描束数字X射线(SBDX)是一种反向几何X射线荧光检查系统,能够与荧光检查同时进行基于断层合成的导管电极3D跟踪。为了方便进行呼吸运动补偿的3D导管跟踪,开发了针对SBDX的自动冠状窦(CS)导管检测算法。该技术使用SBDX的3D定位功能和导管形状的先验知识。代表CS导管的候选点组是从3D形状约束搜索中获得的。然后,在各组中将成本函数最小化,以选择最可能的CS导管候选者。该算法在MATLAB中实现,并使用包含CS导管,消融导管和基准杂波的胸部幻像的记录图像序列进行离线测试。基准位置各不相同,以创建具有挑战性的检测方案。桌子平移和抬高用于模拟运动。 CS导管检测方法在2755帧成像中具有98.1%的真实阳性率和100%的真实阴性率。在具有3.4 GHz CPU和8 GB内存的PC上,平均处理时间为12.7 ms /帧。在具有固定CS导管和沿固定轨迹拉动的消融导管的运动胸模中,演示了基于3D CS导管跟踪的运动补偿。跟踪消融导管轨迹的RMS误差为1.41 mm,而没有运动补偿的误差为10.35 mm。已经开发了一种计算上有效的自动3D CS导管检测方法,以协助进行运动补偿的3D导管跟踪以及将3D心脏模型注册到跟踪的导管中。

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