Publication Date
2012
Document Type
Thesis
Committee Members
Ping He (Committee Member), Nasser H Kashou (Advisor), Julie A Skipper (Committee Member)
Degree Name
Master of Science in Engineering (MSEgr)
Abstract
Super resolution reconstruction (SRR) combines several perspectives of an image (typically low resolution) in order to reconstruct a more complete and comprehensive (higher resolution) image. The aim is to use this concept on magnetic resonance imaging (MRI) data, for which the standard is to scan in several-plane orientation in a 2D fashion. As a result, clinical MRI, functional MRI (FMRI), diffusion weighted imaging (DWI)/diffusion tensor imaging (DTI), and MR angiography (MRA) tend to have high in- plane resolution but low resolution in the slice-select direction. By combining the 2 scans of the orthogonal plane, new 3D images can be reconstructed. This thesis addresses the principal problem of image quality and considers a novel SRR technique that uses the original information from 3 MRI plane orientations in order to enhance the resolution based on prior knowledge of scanning protocol as it relates to voxel resolution. The procedure for validating the MRI data algorithm is executed using MRI dataset of a human brain. The mean squared error (MSE) and peak signal-to-noise ratio (PSNR) were computed for quantitative assessment, whereas the qualitative assessment was performed by visually comparing the SR images to the original HR.
Page Count
123
Department or Program
Department of Biomedical, Industrial & Human Factors Engineering
Year Degree Awarded
2012
Copyright
Copyright 2012, some rights reserved. My ETD may be copied and distributed only for non-commercial purposes and may be modified only if the modified version is distributed with these same permissions. All use must give me credit as the original author.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 License.
