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Parallelization of Non-Rigid Image Registration

dc.contributor.advisorShekhar, Rajen_US
dc.contributor.authorPhilip, Mathewen_US
dc.date.accessioned2010-05-18T05:31:06Z
dc.date.available2010-05-18T05:31:06Z
dc.date.issued2008en_US
dc.identifier.urihttp://hdl.handle.net/1903/10077
dc.description.abstractNon-rigid image registration finds use in a wide range of medical applications ranging from diagnostics to minimally invasive image-guided interventions. Automatic non-rigid image registration algorithms are computationally intensive in that they can take hours to register two images. Although hierarchical volume subdivision-based algorithms are inherently faster than other non-rigid registration algorithms, they can still take a long time to register two images. We show a parallel implementation of one such previously reported and well tested algorithm on a cluster of thirty two processors which reduces the registration time from hours to a few minutes. Mutual information (MI) is one of the most commonly used image similarity measures used in medical image registration and also in the mentioned algorithm. In addition to parallel implementation, we propose a new concept based on bit-slicing to accelerate computation of MI on the cluster and, more generally, on any parallel computing platform such as the Graphics processor units (GPUs). GPUs are becoming increasingly common for general purpose computing in the area of medical imaging as they can execute algorithms faster by leveraging the parallel processing power they offer. However, the standard implementation of MI does not map well to the GPU architecture, leading earlier investigators to compute only an inexact version of MI on the GPU to achieve speedup. The bit-slicing technique we have proposed enables us to demonstrate an exact implementation of MI on the GPU without adversely affecting the speedup.en_US
dc.titleParallelization of Non-Rigid Image Registrationen_US
dc.typeThesisen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.contributor.departmentElectrical Engineeringen_US
dc.subject.pqcontrolledEngineering, Electronics and Electricalen_US
dc.subject.pqcontrolledEngineering, Biomedicalen_US
dc.subject.pquncontrolledClusteren_US
dc.subject.pquncontrolledGPUen_US
dc.subject.pquncontrolledImage Registrationen_US
dc.subject.pquncontrolledMIen_US
dc.subject.pquncontrolledMutual Informationen_US
dc.subject.pquncontrolledParallelizationen_US


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