Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function
| dc.contributor.author | Shehab, Mohammad Mohammad Said | |
| dc.date.accessioned | 2019-04-04T06:37:55Z | |
| dc.date.available | 2019-04-04T06:37:55Z | |
| dc.date.issued | 2018-06 | |
| dc.description.abstract | The Diffusion-Weighted Magnetic Resonance Imaging(DW-MRI) is a promising method for non-invasive investigation of anatomical connectivity in the human brain. The raw data acquired from the MRI scanner may not be directly usable by the specialists. Therefore, new methods are required to make more reasonable representations of the data to extract the required information from them. The initial representation of the MRI data is the huge groups of fibers. These fibers contain fiber crossing bundles, which link the functional brain areas all together as a complex net-work of neural fiber tracts. Q-ball imaging (QBI) is a Diffusion MRI reconstruction technique which has been proven very successful in resolving multiple intravoxel fiber orientations in MRI (i.e., fiber crossing) based on the standard computation of the Orientation Distribution Function (ODF), which is a 3- Dimension spherical function founded to detect the dominant fiber orientations in the underlying volume of a pixel (voxel). This dissertation presents a new method to solve ODF problem through adapting one of the metaheuristic algorithms, namely, Cuckoo Search Algorithm (CSA) for the ODF. The adaptation involved preparing the synthetic data for testing. The results were within the range of previous work and better comparing the other algorithms. However, some shortcomings in the convergence rate and local exploitation were determined and addressed by enhancing with known metaheuristic components. Three successive enhancement versions are proposed tions of various categories. This is to test each version before using it for the ODF. The second step compares against five other methods using synthetic data. The ODFs reconstructed by CSAHC-ODF are sharper and more accurate ODFs than the original image and extracts more accurate maxima. | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/7936 | |
| dc.language.iso | en | en_US |
| dc.publisher | Universiti Sains Malaysia | en_US |
| dc.subject | Cuckoo search algorithm with metaheuristic components | en_US |
| dc.subject | maxima of the orientation distribution function | en_US |
| dc.title | Enhanced Cuckoo Search Algorithm With Metaheuristic Components For Extracting The Maxima Of The Orientation Distribution Function | en_US |
| dc.type | Thesis | en_US |
Files
License bundle
1 - 1 of 1
Loading...
- Name:
- license.txt
- Size:
- 1.71 KB
- Format:
- Item-specific license agreed upon to submission
- Description: