## 1 Introduction  
With a growing geriatric population estimated to triple by 2050, minimally invasive procedures that are image-guided are becoming both more popular and necessary for treating a variety of diseases [1; 2; 3]. Currently, over 400 million individuals worldwide are suffering from cardiovascular disease [4], and the number of annual deaths is estimated to be 23.3 million by 2030 [5]. Of these, well over a million patients will undergo a minimally invasive percutaneous procedure to address a structural heart defect, which is defined as an abnormality of the cardiac wall, valve, chamber, or one of the major arteries of the heart [6]. Despite being minimally invasive, these procedures can still result in death or life-threatening complications due to accidental punctures and device embolization, or can have limited efficacy due to the misalignment of an implanted device [7]. Percutaneousand minimally invasive procedures are used for a wide variety of cardiovascular aliments and are typically guided by imaging modalities, such as X-ray fluoroscopy and echocardiography [8], since they provide real-time imaging [9]. However, most organs are transparent to fluoroscopy, so contrast agents, which transiently opacity structures of interest, must be used to visualize the surrounding tissue. Furthermore, fluoroscopy only provides a two-dimensional (2D) projection of the catheter and device, and, therefore, no information on their depth [10]. Echocardiography can directly image anatomic structures and blood flow, so it is often used as a complementary imaging modality. Although this method can provide useful intraoperative 2D and 3D images, this technology requires skilled operators and general anesthesia is a prerequisite for transesophageal echocardiographic (TEE) guidance. The limitations of these techniques increase the complexity of procedures, which often require the interventionalist to determine the position of the catheter/device by analyzing multiple imaging angles and modalities [11; 12]. The added coordination of different specialties also increases resource utilization and costs. Preoperative 3D imaging modalities provide detailed anatomic information and are often displayed on separate screens or overlaid on real-time imaging modalities to improve image-guided interventions [9; 12; 13]. However, this method of fusion imaging obstructs the view of the real-time image during the procedure [12]. Furthermore, all of these images are displayed on 2D screens, which fundamentally mitigate the ability to perceive depth and orientation [14]. Our group [15; 16; 17], among others [18; 19; 20; 21], have shown the promise of augmented and mixed-reality visualization to address the limitations in depth perception for cardiac interventions by using 3D holographic headsets. In order to leverage mixed-reality technology as a navigation tool for fluoroscopy-guided percutaneous procedures, catheter tracking is a cornerstone of the image guidance system. In our earlier publications, we demonstrated a mixed-reality-based training simulator for structural heart disease interventions using a 3D-printed heart phantom [15]. In this work, the catheter was coupled, at three distinct locations along its distal end, with three electromagnetic (EM) sensors, each allowing the real-time simultaneous tracking of three spatial positions (X, Y, and Z) and three orientation angles (azimuth, elevation, and roll). Although utilizing EM sensors is advantageous for portability and to minimize radiation from fluoroscopy, affordable systems (<USD 10 k) have a low accuracy (up to ~5 mm) and require manual integration of sensors into a catheter, and thus are not a general solution to address the many types of cardiac interventional devices available on the market. To address these limitations with EM sensor tracking, we previously presented a novel deep-learning-driven method for tracking a catheter in a 3D-printed heart phantom from biplane fluoroscopic images that were acquired during a mock procedure [17].