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• W2244512589 abstract "In this dissertation, we present our efforts in developing algorithms in three related areas: (1) unified and optimal tracking, (2) improved motion compensation in cardiovascular MR, and (3) tool tracking in image-guided surgery. With the rapid advancement in the development of tracking algorithms over the years, the choice of tracking methods for a particular application has significantly increased, but it is generally not clear what is the best algorithm to use. Recently popularized sampling kernels have emerged as a flexible design space for developing and merging various tracking algorithms. We demonstrate a connection between kernel-based algorithms and more traditional template tracking methods. This allows for a more efficient optimization (convergence in fewer steps) and naturally extends to objective functions optimizing more complex motion models using multiple spatially distributed kernels. The efficacy of the multi-kernel methods is demonstrated on a variety of tracking examples. In conventional kernel-based tracking approaches, the kernel parameters are selected in an ad-hoc fashion usually leading to sub-optimal tracking results. Thus, we present results pointing toward the design of optimal and approximately optimal target-specific kernels for tracking. In image-guided robot-assisted eye surgery, the dynamic reconstruction of the surgical field that involves the surgical tools and retinal surface and features can greatly improve the effectiveness of human-machine cooperative systems that we have been developing in the Johns Hopkins Engineering Research Center. Thus, we extend the multiple kernel ideas to develop a generic algorithm for reliably tracking thin surgical tools in highly textured backgrounds. Current methods for MR imaging of the cardiac structures, for example coronary arteries and cardiac valves, are limited by the motion artifacts induced by the complex motion of these structures. We present subject-specific motion compensation techniques to improve the speed, quality and reliability of imaging cardiac structures in MR. The underlying principle involves tracking the cardiac structures in motion affected MR images. Thus, we have developed a multiple templatebased tracking method to track these cardiac structures reliably and accurately in a range of MR images. Additionally, we have demonstrated the effectiveness and feasibility of the motion compensation approaches for both coronary MR angiography and cardiac valve MR imaging." @default.
• W2244512589 created "2016-06-24" @default.
• W2244512589 creator A5019201408 @default.
• W2244512589 creator A5089476507 @default.
• W2244512589 date "2008-01-01" @default.
• W2244512589 modified "2023-09-26" @default.
• W2244512589 title "Image-based tracking methods - applications to improved motion compensation in cardiac mr and image-guided surgery" @default.
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