Three-dimensional (3D) transesophageal echocardiography (TEE) is one of the most significant advances in cardiac imaging. Although TEE provides real-time 3D visualization of heart tissues and blood vessels and has no ionizing radiation, x-ray fluoroscopy still dominates in guidance of cardiac interventions due to TEE having a limited field of view and poor visualization of surgical instruments. Therefore, fusing 3D echo with live x-ray images can provide a better guidance solution. This paper proposes a novel framework for image fusion by detecting the pose of the TEE probe in x-ray images in real-time. The framework does not require any manual initialization. Instead it uses a cascade classifier to compute the position and in-plane rotation angle of the TEE probe. The remaining degrees of freedom are determined by fast marching against a template library. The proposed framework is validated on phantoms and patient data. The target registration error for the phantom was 2.1 mm. In addition, 10 patient datasets, seven of which were acquired from cardiac electrophysiology procedures and three from trans-catheter aortic valve implantation procedures, were used to test the clinical feasibility as well as accuracy. A mean registration error of 2.6 mm was achieved, which is well within typical clinical requirements.

三维 (3D) 经食道超声心动图 (TEE) 是心脏成像领域最重要的进步之一。尽管 TEE 提供了心脏组织和血管的实时 3D 可视化，并且没有电离辐射，但由于 TEE 的视野有限且手术器械可视化较差，因此 X 射线透视在心脏介入指导中仍占主导地位。因此，将 3D 回波与实时 X 射线图像融合可以提供更好的制导解决方案。本文通过实时检测 X 射线图像中 TEE 探头的姿态，提出了一种新的图像融合框架。该框架不需要任何手动初始化。相反，它使用级联分类器来计算 TEE 探头的位置和平面内旋转角度。剩余的自由度由对模板库的快速行进确定。提议的框架在体模和患者数据上得到验证。体模的目标配准误差为 2.1 毫米。此外，还使用了 10 个患者数据集，其中 7 个来自心脏电生理程序，3 个来自经导管主动脉瓣植入程序，用于测试临床可行性和准确性。实现了 2.6 毫米的平均配准误差，这完全符合典型的临床要求。其中七个来自心脏电生理程序，三个来自经导管主动脉瓣植入程序，用于测试临床可行性和准确性。实现了 2.6 毫米的平均配准误差，这完全符合典型的临床要求。其中七个来自心脏电生理程序，三个来自经导管主动脉瓣植入程序，用于测试临床可行性和准确性。实现了 2.6 毫米的平均配准误差，这完全符合典型的临床要求。