A multiple catheter tips tracking method in X-ray fluoroscopy images by a new lightweight segmentation network and Bayesian filtering

During percutaneous coronary intervention, the guiding catheter plays an important role. Tracking the catheter tip placed at the coronary ostium in the X-ray fluoroscopy sequence can obtain image displacement information caused by the heart beating, which can help dynamic coronary roadmap overlap on X-ray fluoroscopy images. Due to a low exposure dose, the X-ray fluoroscopy is noisy and low contrast, which causes some difficulties in tracking. In this paper, we developed a new catheter tip tracking framework. First, a lightweight efficient catheter tip segmentation network is proposed and boosted by a self-distillation training mechanism. Then, the Bayesian filtering post-processing method is used to consider the sequence information to refine the single image segmentation results. By separating the segmentation results into several groups based on connectivity, our framework can track multiple catheter tips. The proposed tracking framework is validated on a clinical X-ray sequence dataset.

High-resolution feature based central venous catheter tip detection network in X-ray images

Hospital patients can have catheters and lines inserted during the course of their admission to give medicines for the treatment of medical issues, especially the central venous catheter (CVC). However, malposition of CVC will lead to many complications, even death. Clinicians always detect the malposition based on position detection of CVC tip via X-ray images. To reduce the workload of the clinicians and the percentage of malposition occurrence, we propose an automatic catheter tip detection framework based on a convolutional neural network (CNN). The proposed framework contains three essential components which are modified HRNet, segmentation supervision module, and deconvolution module. The modified HRNet can retain high-resolution features from start to end, ensuring the maintenance of precise information from the X-ray images. The segmentation supervision module can alleviate the presence of other line-like structures such as the skeleton as well as other tubes and catheters used for treatment. In addition, the deconvolution module can further increase the feature resolution on the top of the highest-resolution feature maps in the modified HRNet to get a higher-resolution heatmap of the catheter tip. A public CVC Dataset is utilized to evaluate the performance of the proposed framework. The results show that the proposed algorithm offering a mean Pixel Error of 4.11 outperforms three comparative methods (Ma's method, SRPE method, and LCM method). It is demonstrated to be a promising solution to precisely detect the tip position of the catheter in X-ray images.

A Tensor-based Catheter and Wire Detection and Tracking Framework and Its Clinical Applications

OBJECTIVE

Catheters and wires are used extensively in cardiac catheterization procedures. Detecting their positions in fluoroscopic X-ray images is important for several clinical applications such as motion compensation and co-registration between 2D and 3D imaging modalities. Detecting the complete length of a catheter or wire object as well as electrode positions on the catheter or wire is a challenging task.

METHOD

In this paper, an automatic detection framework for catheters and wires is developed. It is based on path reconstruction from image tensors, which are eigen direction vectors generated from a multiscale vessel enhancement filter. A catheter or a wire object is detected as the smooth path along those eigen direction vectors. Furthermore, a real-time tracking method based on a template generated from the detection method was developed.

RESULTS

The proposed framework was tested on a total of 7,754 X-ray images. Detection errors for catheters and guidewires are 0.56 0.28 mm and 0.68 0.33 mm, respectively. The proposed framework was also tested and validated in two clinical applications. For motion compensation using catheter tracking, the 2D target registration errors (TRE) of 1.8 mm 0.9 mm was achieved. For co-registration between 2D X-ray images and 3D models from MRI images, a TRE of 2.3 0.9 mm was achieved.

CONCLUSION

A novel and fully automatic detection framework and its clinical applications are developed.

SIGNIFICANCE

The proposed framework can be applied to improve the accuracy of image-guidance systems for cardiac catheterization procedures.

Real-time registration of 3D echo to x-ray fluoroscopy based on cascading classifiers and image registration

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.

Robust navigation support in lowest dose image setting

PURPOSE

Clinical cardiac electrophysiology (EP) is concerned with diagnosis and treatment of cardiac arrhythmia describing abnormality or perturbation in the normal activation sequence of the myocardium. With the recent introduction of lowest dose X-ray imaging protocol for EP procedures, interventional image enhancement has gained crucial importance for the well-being of patients as well as medical staff.

METHODS

In this paper, we introduce a novel method to detect and track different EP catheter electrodes in lowest dose fluoroscopic sequences based on [Formula: see text]-sparse coding and online robust PCA (ORPCA). Besides being able to work on real lowest dose sequences, the underlying methodology achieves simultaneous detection and tracking of three main EP catheters used during ablation procedures.

RESULTS

We have validated our algorithm on 16 lowest dose fluoroscopic sequences acquired during real cardiac ablation procedures. In addition to expert labels for 2 sequences, we have employed a crowdsourcing strategy to obtain ground truth labels for the remaining 14 sequences. In order to validate the effect of different training data, we have employed a leave-one-out cross-validation scheme yielding an average detection rate of [Formula: see text].

CONCLUSION

Besides these promising quantitative results, our medical partners also expressed their high satisfaction. Being based on [Formula: see text]-sparse coding and online robust PCA (ORPCA), our method advances previous approaches by being able to detect and track electrodes attached to multiple different catheters.

A novel real-time computational framework for detecting catheters and rigid guidewires in cardiac catheterization procedures

Purpose

Catheters and guidewires are used extensively in cardiac catheterization procedures such as heart arrhythmia treatment (ablation), angioplasty, and congenital heart disease treatment. Detecting their positions in fluoroscopic X‐ray images is important for several clinical applications, for example, motion compensation, coregistration between 2D and 3D imaging modalities, and 3D object reconstruction.

Methods

For the generalized framework, a multiscale vessel enhancement filter is first used to enhance the visibility of wire‐like structures in the X‐ray images. After applying adaptive binarization method, the centerlines of wire‐like objects were extracted. Finally, the catheters and guidewires were detected as a smooth path which is reconstructed from centerlines of target wire‐like objects. In order to classify electrode catheters which are mainly used in electrophysiology procedures, additional steps were proposed. First, a blob detection method, which is embedded in vessel enhancement filter with no additional computational cost, localizes electrode positions on catheters. Then the type of electrode catheters can be recognized by detecting the number of electrodes and also the shape created by a series of electrodes. Furthermore, for detecting guiding catheters or guidewires, a localized machine learning algorithm is added into the framework to distinguish between target wire objects and other wire‐like artifacts. The proposed framework were tested on total 10,624 images which are from 102 image sequences acquired from 63 clinical cases.

Results

Detection errors for the coronary sinus (CS) catheter, lasso catheter ring and lasso catheter body are 0.56 ± 0.28 mm, 0.64 ± 0.36 mm, and 0.66 ± 0.32 mm, respectively, as well as success rates of 91.4%, 86.3%, and 84.8% were achieved. Detection errors for guidewires and guiding catheters are 0.62 ± 0.48 mm and success rates are 83.5%.

Conclusion

The proposed computational framework do not require any user interaction or prior models and it can detect multiple catheters or guidewires simultaneously and in real‐time. The accuracy of the proposed framework is sub‐mm and the methods are robust toward low‐dose X‐ray fluoroscopic images, which are mainly used during procedures to maintain low radiation dose.

Acousto-Optic Catheter Tracking Sensor for Interventional MRI Procedures

OBJECTIVE

The objective of this paper is to introduce an acousto-optic optical fiber sensor for tracking catheter position during interventional magnetic resonance imaging (MRI) to overcome RF induced heating of active markers.

METHODS

The sensor uses a miniature coil coupled to a piezoelectric transducer, which is in turn mechanically connected to an optical fiber. The piezoelectric transducer converts the RF signal to acoustic waves in the optical fiber over a region including a fiber Bragg grating (FBG). The elastic waves in the fiber modulates the FBG geometry and hence the reflected light in the optical fiber. Since the coil is much smaller than the RF wavelength and the signal is transmitted on the dielectric optical fiber, the sensor effectively reduces RF induced heating risk. Proof of concept prototypes of the sensor are implemented using commercially available piezoelectric transducers and optical fibers with FBGs. The prototypes are characterized in a 1.5 T MRI system in comparison with an active tracking marker.

RESULTS

Acousto-optical sensor shows linear response with flip angle and it can be used to detect signals from multiple coils for potential orientation detection. It has been successfully used to detect the position of a tacking coil in phantom in an imaging experiment.

CONCLUSION

Acousto-optical sensing is demonstrated for tracking catheters during interventional MRI. Real-time operation of the sensor requires sensitivity improvements like using a narrow band FBG.

SIGNIFICANCE

Acousto-optics provides a compact solution to sense RF signals in MRI with dielectric transmission lines.

Feedforward Coordinate Control of a Robotic Cell Injection Catheter

Remote and robotically actuated catheters are the stepping-stones toward autonomous catheters, where complex intravascular procedures may be performed with minimal intervention from a physician. This article proposes a concept for the positional, feedforward control of a robotically actuated cell injection catheter used for the injection of myogenic or undifferentiated stem cells into the myocardial infarct boundary zones of the left ventricle. The prototype for the catheter system was built upon a needle-based catheter with a single degree of deflection, a 3-D printed handle combined with actuators, and the Arduino microcontroller platform. A bench setup was used to mimic a left ventricle catheter procedure starting from the femoral artery. Using Matlab and the open-source video modeling tool Tracker, the planar coordinates (y, z) of the catheter position were analyzed, and a feedforward control system was developed based on empirical models. Using the Student’s t test with a sample size of 26, it was determined that for both the y- and z-axes, the mean discrepancy between the calibrated and theoretical coordinate values had no significant difference compared to the hypothetical value of µ = 0. The root mean square error of the calibrated coordinates also showed an 88% improvement in the z-axis and 31% improvement in the y-axis compared to the unmodified trial run. This proof of concept investigation leads to the possibility of further developing a feedfoward control system in vivo using catheters with omnidirectional deflection. Feedforward positional control allows for more flexibility in the design of an automated catheter system where problems such as systemic time delay may be a hindrance in instances requiring an immediate reaction.

Photoacoustic-based catheter tracking: simulation, phantom, and in vivo studies

Catheters are commonly used in many procedures and tracking and localizing them is critical to patient safety and surgical success. The standard of care for catheter tracking is with the use of fluoroscopy. Alternatives using conventional tracking technologies such as electromagnetic trackers have been previously explored. This work explores the use of an emerging imaging modality, photoacoustics, as a means for tracking. A piezoelectric (PZT) sensor is placed at the tip of the catheter, allowing it to receive the acoustic signals generated from photoacoustic markers due to the photoacoustic effect. The locations of these photoacoustic markers are determined by a stereo-camera and the received acoustic signals are converted into distances between the PZT element and the photoacoustic markers. The location of the PZT sensor can be uniquely determined following a multilateration process. This work validates this photoacoustic tracking method in phantom, simulation, and in vivo scenarios using metrics including reconstruction precision, relative accuracy, estimated accuracy, and leave-out accuracy. Submillimeter tracking results were achieved in phantom experiments. Simulation studies evaluated various physical parameters relating to the photoacoustic source and the PZT sensor. In vivo results showed feasibility for the eventual deployment of this technology.

Computer-aided detection of retained surgical needles from postoperative radiographs

PURPOSE

Foreign objects, such as surgical sponges, needles, sutures, and other surgical instruments, retained in the patient's body can have dire consequences in terms of patient mortality as well as legal and financial penalties. We propose computer-aided detection (CAD) on postoperative radiographs as a potential solution to reduce the chance of retained foreign objects (RFOs) after surgery, thus alleviating one of the major concerns for patient safety in the operation room. A CAD system can function as a second pair of eyes or a prescreener for the surgeon and radiologist, depending on the CAD system design and the workflow. In this work, we focus on the detection of surgical needles on postoperative radiographs. As needles are frequently observed RFOs, a CAD system that can offer high sensitivity and specificity toward detecting surgical needles will be useful.

METHODS

Our CAD system incorporates techniques such as image segmentation, image enhancement, feature analysis, and curve fitting to detect surgical needles on radiographs. A dataset consisting of 108 cadaver images with a total of 116 needles and 100 cadaver "normal" images without needles was acquired with a portable digital x-ray system. A reference standard was obtained by marking the needle locations using an in-house developed graphical user interface. The 108 cadaver images with the needles were partitioned into a training set containing 53 cadaver images with 59 needles and a test set containing 55 cadaver images with 57 needles. All of the 100 cadaver normal images were reserved as a part of the test set and used to estimate the false-positive detection rate. Two operating points were chosen from the CAD system such that it can be operated in two modes, one with higher specificity (mode I) and the other with higher sensitivity (mode II).

RESULTS

For the training set, the CAD system with the rule-based classifier achieved a sensitivity of 74.6% with 0.15 false positives per image (FPs/image) in mode I and a sensitivity of 89.8% with 0.36 FPs/image in mode II. For the test set, the CAD system achieved a sensitivity of 77.2% with 0.26 FPs/image in mode I and a sensitivity of 84.2% with 0.6 FPs/image in mode II. For comparison, the CAD system with the neural network classifier achieved a sensitivity of 74.6% with 0.08 FPs/image in mode I and a sensitivity of 88.1% with 0.28 FPs/image in mode II for the training set, and a sensitivity of 75.4% with 0.23 FPs/image in mode I and a sensitivity of 86.0% with 0.57 FPs/image in mode II for the test set.

CONCLUSION

A novel CAD system has been developed for automated detection of needles inadvertently left behind in a patient's body from postsurgery radiographs. The pilot system offers reasonable performance in both the high sensitivity and high specificity modes. This preliminary study shows the promise of CAD as a low-cost and efficient aid for reducing retained surgical needles in patients.

Robust catheter identification and tracking in X-ray angiographic sequences

Coronary artery disease (CAD) is one of the major causes of death worldwide. Today X-ray angiography is a standard method for CAD diagnosis. Usually, the quality of these images is not good enough. Noise, camera and heart motions, non-uniform illumination and even the presence of catheter are sources of quality degradation. The existence of catheter can produce difficulties in vessel extraction methods because catheter is structurally similar to arteries. In this paper we propose a fully automatic method for catheter detection and tracking during the whole angiography sequence. In this method with a vesselness map, we smooth each frame using guided filter. The catheter is detected in the first frame using Hough transform. We then fit a second order polynomial on the catheter and accurately track it throughout the sequence. Our method is tested on 25 X-ray angiography sequences where a precision of 0.9597 is achieved.

Significant radiation reduction in interventional fluoroscopy using a novel eye controlled movable region of interest

PURPOSE

This paper reports the first results obtained using a novel technology called eye controlled region of interest (ECR) that substantially reduces both staff and patient irradiation during an interventional fluoroscopy procedure without interfering with workflow. Its collimator includes a partially x-ray attenuating plate with a nonattenuating aperture. An eye tracker follows the operator's gaze to automatically position the aperture to the clinical region of interest (CROI) anywhere in the image in real-time.

METHODS

Experiments were performed in a swine model using a mobile fluoroscope with a 30 cm image intensifier and manual control of fluoroscopic factors. The factory collimator and image display monitor were replaced with different components for this study. The full 30 cm field-of-view (FOV) of the image intensifier was irradiated at normal levels, and served as a baseline, when ECR was disengaged. With ECR engaged, most of the 30 cm FOV was irradiated to less than 20% of normal levels while the CROI was normally irradiated. Animal irradiation was determined by physical KAP (kerma area product) measurements. Operator irradiation was characterized by air kerma and air kerma rate measurements near the operator. Data were collected from three pairs of interventions in each of five swine models.

RESULTS

When ECR was engaged, KAP was reduced to 0.22 (p < 0.001) of baseline and operator irradiation to 0.27 (p < 0.001) of baseline. Overall procedure time had a borderline increase (p = 0.07) but fluoroscopy time was unchanged (p = 0.36) (Wilcoxon signed rank). Measured staff and patient radiation reductions are consistent with this collimator's design. Subjective impressions of imaging improvements are consistent with less scatter reaching the CROI. Engaging ECR reduced irradiation without subjectively or objectively increasing operator workload.

CONCLUSIONS

The first in vivo evaluation of ECR demonstrated that this technology has objectively reduced KAP and operator irradiation by approximately 75% without interfering with the performance of fluoroscopically guided interventional procedures. In addition, reduced scatter production subjectively improved device visualization. These findings indicate the practicability of achieving better radiation optimization.

Electrophysiology Catheter Detection and Reconstruction From Two Views in Fluoroscopic Images

Electrophysiology (EP) studies and catheter ablation have become important treatment options for several types of cardiac arrhythmias. We present a novel image-based approach for automatic detection and 3-D reconstruction of EP catheters where the physician marks the catheter to be reconstructed by a single click in each image. The result can be used to provide 3-D information for enhanced navigation throughout EP procedures. Our approach involves two X-ray projections acquired from different angles, and it is based on two steps: First, we detect the catheter in each view after manual initialization using a graph-search method. Then, the detection results are used to reconstruct a full 3-D model of the catheter based on automatically determined point pairs for triangulation. An evaluation on 176 different clinical fluoroscopic images yielded a detection rate of 83.4%. For measuring the error, we used the coupling distance which is a more accurate quality measure than the average point-wise distance to a reference. For successful outcomes, the 2-D detection error was 1.7 mm ±1.2 mm. Using successfully detected catheters for reconstruction, we obtained a reconstruction error of 1.8 mm ±1.1 mm on phantom data. On clinical data, our method yielded a reconstruction error of 2.2 mm ±2.2 mm.

Automatic 3D reconstruction of electrophysiology catheters from two-view monoplane C-arm image sequences

PURPOSE

Catheter guidance is a vital task for the success of electrophysiology interventions. It is usually provided through fluoroscopic images that are taken intra-operatively. The cardiologists, who are typically equipped with C-arm systems, scan the patient from multiple views rotating the fluoroscope around one of its axes. The resulting sequences allow the cardiologists to build a mental model of the 3D position of the catheters and interest points from the multiple views.

METHOD

We describe and compare different 3D catheter reconstruction strategies and ultimately propose a novel and robust method for the automatic reconstruction of 3D catheters in non-synchronized fluoroscopic sequences. This approach does not purely rely on triangulation but incorporates prior knowledge about the catheters. In conjunction with an automatic detection method, we demonstrate the performance of our method compared to ground truth annotations.

RESULTS

In our experiments that include 20 biplane datasets, we achieve an average reprojection error of 0.43 mm and an average reconstruction error of 0.67 mm compared to gold standard annotation.

CONCLUSIONS

In clinical practice, catheters suffer from complex motion due to the combined effect of heartbeat and respiratory motion. As a result, any 3D reconstruction algorithm via triangulation is imprecise. We have proposed a new method that is fully automatic and highly accurate to reconstruct catheters in three dimensions.

3D localization of electrophysiology catheters from a single x-ray cone-beam projection

PURPOSE

X-ray images allow the visualization of percutaneous devices such as catheters in real time but inherently lack depth information. The provision of 3D localization of these devices from cone beam x-ray projections would be advantageous for interventions such as electrophysiology (EP), whereby the operator needs to return a device to the same anatomical locations during the procedure. A method to achieve real-time 3D single view localization (SVL) of an object of known geometry from a single x-ray image is presented. svl exploits the change in the magnification of an object as its distance from the x-ray source is varied. The x-ray projection of an object of interest is compared to a synthetic x-ray projection of a model of said object as its pose is varied.

METHODS

svl was tested with a 3 mm spherical marker and an electrophysiology catheter. The effect of x-ray acquisition parameters on svl was investigated. An independent reference localization method was developed to compare results when imaging a catheter translated via a computer controlled three-axes stage. svl was also performed on clinical fluoroscopy image sequences. A commercial navigation system was used in some clinical image sequences for comparison.

RESULTS

svl estimates exhibited little change as x-ray acquisition parameters were varied. The reproducibility of catheter position estimates in phantoms denoted by the standard deviations, (σ(x), σ(y), σ(z)) = (0.099 mm,  0.093 mm,  2.2 mm), where x and y are parallel to the detector plane and z is the distance from the x-ray source. Position estimates (x, y, z) exhibited a 4% systematic error (underestimation) when compared to the reference method. The authors demonstrated that EP catheters can be tracked in clinical fluoroscopic images.

CONCLUSIONS

It has been shown that EP catheters can be localized in real time in phantoms and clinical images at fluoroscopic exposure rates. Further work is required to characterize performance in clinical images as well as the sensitivity to clinical image quality.

Real-Time MRI-Guided Catheter Tracking Using Hyperpolarized Silicon Particles

Visualizing the movement of angiocatheters during endovascular interventions is typically accomplished using x-ray fluoroscopy. There are many potential advantages to developing magnetic resonance imaging-based approaches that will allow three-dimensional imaging of the tissue/vasculature interface while monitoring other physiologically-relevant criteria, without exposing the patient or clinician team to ionizing radiation. Here we introduce a proof-of-concept development of a magnetic resonance imaging-guided catheter tracking method that utilizes hyperpolarized silicon particles. The increased signal of the silicon particles is generated via low-temperature, solid-state dynamic nuclear polarization, and the particles retain their enhanced signal for ≥ 40 minutes--allowing imaging experiments over extended time durations. The particles are affixed to the tip of standard medical-grade catheters and are used to track passage under set distal and temporal points in phantoms and live mouse models. With continued development, this method has the potential to supplement x-ray fluoroscopy and other MRI-guided catheter tracking methods as a zero-background, positive contrast agent that does not require ionizing radiation.

Online tracking of interventional devices for endovascular aortic repair

PURPOSE

The continuous integration of innovative imaging modalities into conventional vascular surgery rooms has led to an urgent need for computer assistance solutions that support the smooth integration of imaging within the surgical workflow. In particular, endovascular interventions performed under 2D fluoroscopic or angiographic imaging only, require reliable and fast navigation support for complex treatment procedures such as endovascular aortic repair. Despite the vast variety of image-based guide wire and catheter tracking methods, an adoption of these for detecting and tracking the stent graft delivery device is not possible due to its special geometry and intensity appearance.

METHODS

In this paper, we present, for the first time, the automatic detection and tracking of the stent graft delivery device in 2D fluoroscopic sequences on the fly. The proposed approach is based on the robust principal component analysis and extends the conventional batch processing towards an online tracking system that is able to detect and track medical devices on the fly.

RESULTS

The proposed method has been tested on interventional sequences of four different clinical cases. In the lack of publicly available ground truth data, we have further initiated a crowd sourcing strategy that has resulted in 200 annotations by unexperienced users, 120 of which were used to establish a ground truth dataset for quantitatively evaluating our algorithm. In addition, we have performed a user study amongst our clinical partners for qualitative evaluation of the results.

CONCLUSIONS

Although we calculated an average error in the range of nine pixels, the fact that our tracking method functions on the fly and is able to detect stent grafts in all unfolding stages without fine-tuning of parameters has convinced our clinical partners and they all agreed on the very high clinical relevance of our method.

Fully automatic catheter localization in C-arm images using ł1-sparse coding

We propose a method to perform automatic detection and tracking of electrophysiology (EP) catheters in C-arm fluoroscopy sequences. Our approach does not require any initialization, is completely automatic, and can concurrently track an arbitrary number of overlapping catheters. After a pre-processing step, we employ sparse coding to first detect candidate catheter tips, and subsequently detect and track the catheters. The proposed technique is validated on 2835 C-arm images, which include 39,690 manually selected ground-truth catheter electrodes. Results demonstrated sub-millimeter detection accuracy and real-time tracking performances.

6DoF catheter detection, application to intracardiac echocardiography

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.