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.
| Identifer | oai:union.ndltd.org:wpi.edu/oai:digitalcommons.wpi.edu:etd-dissertations-1280 |
| Date | 09 May 2005 |
| Creators | Yu, Hongliang |
| Contributors | Zhikun Hou, Committee Member, , |
| Publisher | Digital WPI |
| Source Sets | Worcester Polytechnic Institute |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Doctoral Dissertations (All Dissertations, All Years) |
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