PERCEPTION AND CONTROL OF AN MRI-GUIDED ROBOTIC CATHETER IN DEFORMABLE ENVIRONMENTS
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| Title: | PERCEPTION AND CONTROL OF AN MRI-GUIDED ROBOTIC CATHETER IN DEFORMABLE ENVIRONMENTS |
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| Authors: | Tuna, Eser Erdem |
| Advisors: | Cavusoglu, Murat Cenk |
| Committee Members: | Cavusoglu, Murat Cenk |
| Summary: | For the last decade, robotic catheters have emerged as a promising technology for catheter ablation. The development of magnetic resonance image (MRI) guided robotic catheters is complicated by the need to track the position and orientation of these instruments within the MRI scanner, accurate localization of the desired target on cardiac surface, and precise control of the catheter. In order to accurately navigate the catheter to the desired location on the heart via MR images, it is necessary to register the robot space to the MR scanner's image space as well as track the catheter position and the cardiac surface motion from the MR images, while precisely controlling the catheter. This thesis details novel approaches to address the challenges in these topics.The first contribution of this work is to describe a framework to register robotic catheter to the MRI scanner, while taking into account the scanner related geometric distortions in the MR images. The geometric distortion is identified via a grid-based, custom-built 3D phantom, where morphological operations are applied to localize the control points in the phantom images, which in turn are used to determine the distortion map. The underlying distortion is modeled and corrected by employing thin plate splines. The catheter to scanner registration is performed via a differential, multi-slice image-based registration approach utilizing active fiducial coils. 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 MR 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 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 within the workspace, employing multi-planar capabilities of the MRI scanner.The second contribution of this work is to present a particle filter based framework to track cardiac surface motion from a time sequence of single MRI slices by utilizing a low-order parametric deformable model of the cardiac surface. Cardiac surface motion is represented as a stochastic dynamic system. Deformable models are utilized to introduce shape prior to control the extent of the deformations. Dynamic model of the system uses adaptive filters to model complex heart motion. Particle filters are employed to recursively estimate current system state over time. The proposed method is applied to recover biventricular deformations and validated with a numerical phantom and a real cardiac MRI dataset. The algorithm is evaluated with multiple experiments using fixed and varying image slice planes at each time step.The final contributions are a set of approaches to perform the free-space open-loop dynamic response analysis of an MRI-guided robotic catheter system and to track the robotic catheter from the MRI images. A pendulum model is employed to describe the underlying nonlinearity in the catheter system and to perform an approximate input-output linearization. Then, a black-box system identification approach is utilized 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. A particle filter based framework is presented to track the catheter from MR images. The motion model of the catheter is based on the quasi-static kinematics of the catheter. The measurement model calculates the weights of the particles from the detected position of the catheter in the MR images and the predicted position calculated from the catheter configuration. The feasibility of the algorithm is demonstrated via simulations.The presented work paves the way for effective and accurate free-space closed-loop control of the robotic catheter with real-time feedback from MRI guidance. |
| URL: | http://rave.ohiolink.edu/etdc/view?acc_num=case1619795928790909 |
| Database: | OpenDissertations |
| Abstract: | For the last decade, robotic catheters have emerged as a promising technology for catheter ablation. The development of magnetic resonance image (MRI) guided robotic catheters is complicated by the need to track the position and orientation of these instruments within the MRI scanner, accurate localization of the desired target on cardiac surface, and precise control of the catheter. In order to accurately navigate the catheter to the desired location on the heart via MR images, it is necessary to register the robot space to the MR scanner's image space as well as track the catheter position and the cardiac surface motion from the MR images, while precisely controlling the catheter. This thesis details novel approaches to address the challenges in these topics.The first contribution of this work is to describe a framework to register robotic catheter to the MRI scanner, while taking into account the scanner related geometric distortions in the MR images. The geometric distortion is identified via a grid-based, custom-built 3D phantom, where morphological operations are applied to localize the control points in the phantom images, which in turn are used to determine the distortion map. The underlying distortion is modeled and corrected by employing thin plate splines. The catheter to scanner registration is performed via a differential, multi-slice image-based registration approach utilizing active fiducial coils. 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 MR 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 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 within the workspace, employing multi-planar capabilities of the MRI scanner.The second contribution of this work is to present a particle filter based framework to track cardiac surface motion from a time sequence of single MRI slices by utilizing a low-order parametric deformable model of the cardiac surface. Cardiac surface motion is represented as a stochastic dynamic system. Deformable models are utilized to introduce shape prior to control the extent of the deformations. Dynamic model of the system uses adaptive filters to model complex heart motion. Particle filters are employed to recursively estimate current system state over time. The proposed method is applied to recover biventricular deformations and validated with a numerical phantom and a real cardiac MRI dataset. The algorithm is evaluated with multiple experiments using fixed and varying image slice planes at each time step.The final contributions are a set of approaches to perform the free-space open-loop dynamic response analysis of an MRI-guided robotic catheter system and to track the robotic catheter from the MRI images. A pendulum model is employed to describe the underlying nonlinearity in the catheter system and to perform an approximate input-output linearization. Then, a black-box system identification approach is utilized 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. A particle filter based framework is presented to track the catheter from MR images. The motion model of the catheter is based on the quasi-static kinematics of the catheter. The measurement model calculates the weights of the particles from the detected position of the catheter in the MR images and the predicted position calculated from the catheter configuration. The feasibility of the algorithm is demonstrated via simulations.The presented work paves the way for effective and accurate free-space closed-loop control of the robotic catheter with real-time feedback from MRI guidance. |
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