Title page for ETD etd-050905-100341

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
Abstract 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.
Files	Thesis_victor.pdf

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