This study presents a particle filter based framework to track cardiac surface from a time sequence of single magnetic resonance imaging (MRI) slices with the future goal of utilizing the presented ...framework for interventional cardiovascular magnetic resonance procedures, which rely on the accurate and online tracking of the cardiac surface from MRI data. The framework exploits a low-order parametric deformable model of the cardiac surface. A stochastic dynamic system represents the cardiac surface motion. Deformable models are employed to introduce shape prior to control the degree of the deformations. Adaptive filters are used to model complex cardiac motion in the dynamic model of the system. Particle filters are utilized to recursively estimate the current state of the system over time. The proposed method is applied to recover biventricular deformations and validated with a numerical phantom and multiple real cardiac MRI datasets. The algorithm is evaluated with multiple experiments using fixed and varying image slice planes at each time step. For the real cardiac MRI datasets, the average root-mean-square tracking errors of 2.61 mm and 3.42 mm are reported respectively for the fixed and varying image slice planes. This work serves as a proof-of-concept study for modeling and tracking the cardiac surface deformations via a low-order probabilistic model with the future goal of utilizing this method for the targeted interventional cardiac procedures under MR image guidance. For the real cardiac MRI datasets, the presented method was able to track the points-of-interests located on different sections of the cardiac surface within a precision of 3 pixels. The analyses show that the use of deformable cardiac surface tracking algorithm can pave the way for performing precise targeted intracardiac ablation procedures under MRI guidance. The main contributions of this work are twofold. First, it presents a framework for the tracking of whole cardiac surface from a time sequence of single image slices. Second, it employs adaptive filters to incorporate motion information in the tracking of nonrigid cardiac surface motion for temporal coherence.
Robotic-assisted beating heart surgery aims to allow surgeons to operate on a beating heart without stabilizers as if the heart is stationary. The robot actively cancels heart motion by closely ...following a point of interest (POI) on the heart surface - a process called active relative motion canceling. Due to the high bandwidth of the POI motion, it is necessary to supply the controller with an estimate of the immediate future of the POI motion over a prediction horizon in order to achieve sufficient tracking accuracy. In this paper, two least-squares-based prediction algorithms, using an adaptive filter to generate future position estimates, are implemented and studied. The first method assumes a linear system relation between the consecutive samples in the prediction horizon. On the contrary, the second method performs this parametrization independently for each point over the whole the horizon. The effects of predictor parameters and variations in heart rate on tracking performance are studied with constant and varying heart rate data. The predictors are evaluated using a three-degree-of-freedom (DOF) test bed and prerecorded in vivo motion data. Then, the one-step prediction and tracking performances of the presented approaches are compared with an extended Kalman filter predictor. Finally, the essential features of the proposed prediction algorithms are summarized.
This paper presents a free-space open-loop dynamic response analysis for an MRI -guided magnetically-actuated steerable intra-vascular catheter system. The catheter tip is embedded with a set of ...current carrying micro-coils. The catheter is directly actuated via the magnetic torques generated on these coils by the magnetic field of the magnetic resonance imaging (MRI)scanner. The relationship between the input current commands and catheter tip deflection angle presents an inherent nonlinearity in the proposed catheter system. The system nonlinearity is analyzed by utilizing a pendulum model. The pendulum model is used to describe the system nonlinearity and to perform an approximate input-output linearization. Then, a black-box system identification approach is performed for frequency response analysis of the linearized dynamics. The optimal estimated model is reduced by observing the modes and considering the Nyquist frequency of the camera system that is used to track the catheter motion. The reduced model is experimentally validated with 3D open-loop Cartesian free-space trajectories. This study paves the way for effective and accurate free-space closed-loop control of the robotic catheter with real-time feedback from MRI guidance in subsequent research.
Magnetic resonance imaging (MRI) guided robotic procedures require safe robotic instrument navigation and precise target localization. This depends on reliable tracking of the instrument from MR ...images, which requires accurate registration of the robot to the scanner. A novel differential image based robot-to-MRI scanner registration approach is proposed that utilizes a set of active fiducial coils, where background subtraction method is employed for coil detection. In order to use the presented preoperative registration approach jointly with the real-time high speed MRI image acquisition and reconstruction methods in real-time interventional procedures, the effects of the geometric MRI distortion in robot to scanner registration is analyzed using a custom distortion mapping algorithm. The proposed approach is validated by a set of target coils placed within the workspace, employing multi-planar capabilities of the scanner. Registration and validation errors are respectively 2.05 mm and 2.63 mm after the distortion correction showing an improvement of respectively 1.08 mm and 0.14 mm compared to the results without distortion correction.
In magnetic resonance imaging (MRI) guided robotic catheter ablation procedures, reliable tracking of the catheter within the MRI scanner is needed to safely navigate the catheter. This requires ...accurate registration of the catheter to the scanner. This paper presents a differential, multi-slice image-based registration approach utilizing active fiducial coils. The proposed method would be used to pre-operatively register the MRI image space with the physical catheter space. In the proposed scheme, the registration is performed with the help of a registration frame, which has a set of embedded electromagnetic coils designed to actively create MRI image artifacts. These coils are detected in the MRI scanner's coordinate system by background subtraction. The detected coil locations in each slice are weighted by the artifact size and then registered to known ground truth coil locations in the catheter's coordinate system via least-squares fitting. The proposed approach is validated by using a set of target coils placed withing the workspace, employing multi-planar capabilities of the MRI scanner. The average registration and validation errors are respectively computed as 1.97 mm and 2.49 mm. The multi-slice approach is also compared to the single-slice method and shown to improve registration and validation by respectively 0.45 mm and 0.66 mm.
In robotic assisted beating heart surgery, the control architecture for heart motion tracking has stringent requirements in terms of bandwidth of the motion that needs to be tracked. In order to ...achieve sufficient tracking accuracy, feed-forward control algorithms, which rely on estimations of upcoming heart motion, have been proposed in the literature. However, performance of these feed-forward motion control algorithms under heart rhythm variations is an important concern. In their past work, the authors have demonstrated the effectiveness of a receding horizon model predictive control-based algorithm, which used generalized adaptive predictors, under constant and slowly varying heart rate conditions. This paper extends these studies to the case when the heart motion statistics change abruptly and significantly, such as during arrhythmias. A feasibility study is carried out to assess the motion tracking capabilities of the adaptive algorithms in the occurrence of arrhythmia during beating heart surgery. Specifically, the tracking performance of the algorithms is evaluated on prerecorded motion data, which is collected in vivo and includes heart rhythm irregularities. The algorithms are tested using both simulations and bench experiments on a three degree-of-freedom robotic test bed. They are also compared with a position-plus-derivative controller as well as a receding horizon model predictive controller that employs an extended Kalman filter algorithm for predicting future heart motion.
In robotic assisted beating heart surgery, the goal is to develop a robotic system that can actively cancel heart motion by closely following a point of interest (POI) on the heart surface, a process ...called Active Relative Motion Canceling (ARMC). In order to track and cancel POI motion precisely, control algorithms require good quality heart motion data. In this paper, a novel method is described which uses a particle filter to estimate the three-dimensional location of POI on heart surface by using measurements obtained from sonomicrometry along with an accelerometer. The new method employs a differential probability approach to increase the accuracy of the particle filter. The performance of the proposed method is evaluated by simulations.
One of the critical components of robotic-assisted beating heart surgery is precise localization of a point-of-interest (POI) position on cardiac surface, which needs to be tracked by the robotic ...instruments. This is challenging as the incoming sensor measurements, from which POI position is localized, might be noisy and incomplete. This paper presents two Bayesian filtering based localization approaches to localize POI position online from sonomicrometer measurements. Specifically, extended Kalman filter (EKF) and particle filter (PF) localization algorithms are explored to estimate the state of POI position. The estimations of upcoming heart motion generated by the generalized adaptive predictor, which is demonstrated in the authors' past work, are also incorporated to generate an improved motion model. The proposed methods are validated with prerecorded in-vivo heart motion data.
Abstract Objective The objective is to compare the analgesic effects of diclofenac, acetaminophen, and acupuncture in urolithiasis-driven renal colic pain relief. Methods Renal colic patients were ...divided randomly into 3 groups. Patients in group I (n = 40) were treated with intravenous acetaminophen, those in group II (n = 41) with acupuncture, and those in group III (n = 40) with a 75-mg intramuscular injection diclofenac sodium. Visual analogue scale (VAS) and verbal rating scale (VRS) were used to assess pain intensity after 10, 30, 60, and 120 minutes. Results No significant differences in baseline VAS or VRS were found with regard to age or sex. After 10 minutes, all 3 groups experienced a significant decrease in VAS and VRS scores, with the most drastic decrease occurring in group II. After 30 minutes, there was a significantly higher decrease in group III than in group I ( P = .001). After 60 minutes, mean VAS scores of groups I and III ( P = .753) were similar. The mean VAS score of group III was lower than that of group II ( P = .013). After 120 minutes, the difference in the VAS scores was ( P = .000) between groups I and II and between groups II and III. Yet, the VAS evaluation made after 120 minutes revealed statistically similar outcomes for groups I and III ( P = .488). The statistical findings for VRS evaluations made after 10, 30, 60, and 120 were similar to those for VAS. Conclusions In renal colic patients with a possible nonsteroidal anti-inflammatory drug and acetaminophen side effect risk, acupuncture emerges as an alternative treatment modality.
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