Document Type dissertation Author Name Yu, Hongliang URN etd-050905-100341 Title Automatic Rigid and Deformable Medical Image Registration Degree PhD Department Mechanical Engineering Advisors John Sullivan, Advisor Allen Hoffman, Committee Member Reinhold Ludwig, Committee Member Gretar Tryggvason, Committee Member Zhikun Hou, Graduate Committee Rep Keywords image registration Date of Presentation/Defense 2005-05-04 Availability unrestricted
In this research three innovative registration systems were designed with the configurations of the mutual information and optimization technique: (1) mutual information combined with the downhill simplex method of optimization. (2) the derivative of mutual information combined with Quasi-Newton method. (3) mutual information combined with hybrid genetic algorithm (large-space random search) to avoid local maximum during the optimization. These automatic registration systems were evaluated with a variety of images, dimensions and voxel resolutions. Experiments demonstrate that registration system combined with mutual information and hybrid genetic algorithm can provide robust and accurate alignments to obtain a composite activation map for functional MRI analysis.
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