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6DoF Catheter Detection, Application to Intracardiac Echocardiography

机译:6DoF导管检测,在心内超声检查中的应用

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摘要

Hybrid imaging systems, consisting of fluoroscopy and echocardiography, are increasingly selected for intra-operative support of minimally invasive cardiac interventions. Intracardiac echocardiograpy (ICE) is an emerging modality with the promise of removing sedation or general anesthesia associated with transesophageal echocardiography (TEE). We introduce a novel 6 degrees of freedom (DoF) pose estimation approach for catheters (equipped with radiopaque ball markers) in single X-Ray fluoroscopy projection and investigate the method's application to a prototype ICE catheter. Machine learning based catheter detection is implemented in a Bayesian hypothesis fusion framework, followed by refinement of ball marker locations through template matching. Marker correspondence and 3D pose estimation are solved through iterative optimization. The method registers the ICE volume to the C-arm coordinate system. Experiments are performed on synthetic and porcine in-vivo data. Target registration error (TRE), defined in the echo cone, is the basis of our preliminary evaluation. The method reached 8.06 ±7.2 mm TRE on 703 cases. Potential uses of our hybrid system include structural heart disease interventions and electrophysiologycal mapping or catheter ablation procedures.
机译:越来越多地选择由荧光检查和超声心动图组成的混合成像系统,以在术中支持微创心脏干预。心内超声心动图检查(ICE)是一种新兴的治疗手段,有望消除经食道超声心动图检查(TEE)引起的镇静或全身麻醉。我们介绍了一种新颖的6自由度(DoF)姿势估计方法,用于在单个X射线荧光透视投影中测量导管(配备了不透射线的球标记),并研究了该方法在原型ICE导管中的应用。在贝叶斯假设融合框架中实施基于机器学习的导管检测,然后通过模板匹配优化球形标记的位置。标记对应和3D姿势估计通过迭代优化解决。该方法将ICE体积注册到C臂坐标系中。对合成和猪体内数据进行实验。回波锥中定义的目标配准误差(TRE)是我们初步评估的基础。该方法在703例病例中达到8.06±7.2 mm TRE。我们的混合动力系统的潜在用途包括结构性心脏病干预和电生理图或导管消融程序。

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