VGU RESEARCH REPOSITORY
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Title: | Compressed sensing in magnetic resonance imaging | Authors: | Nguyen Bao Lam | Keywords: | Magnetic resonance imaging (MRI);Functional magnetic resonance imaging (FMRI);K-t FOCUSS;Basis pursuit;Compressed sensing | Issue Date: | 2016 | Publisher: | Vietnamese-German University | Abstract: | Magnetic resonance imaging (MRI) is an effective technique used in radiology to image the anatomy and the physiological processes of the body in both health and disease. Functional magnetic resonance imaging or functional MRI (FMRI) is a functional neuroimaging procedure using MR1 technology that measures brain activity by detecting changes associated with blood flow. This thesis conveys a literature review of MR! and fMRI as well as the method for reconstructing undersampled images. The chosen method is Compressed Sensing, which in theory is able to perfectly reconstruct signals with sampling rates dramatically smaller than the Nyquist sampling rate by exploiting the sparsity of signals. In the scope of this thesis, the main focus is to evaluate the effectiveness of compressed sensing implemented in MR1 and MR'. The evaluation will be done and demonstrated with MATLAB and the algorithm used for Compressed Sensing is the k-t FOCUSS. |
URI(1): | http://epub.vgu.edu.vn/handle/dlibvgu/585 | Rights: | Attribution-NonCommercial 4.0 International |
Appears in Collections: | Electrical Engineering and Information Technology (EEIT) |
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Compressed sensing in magnetic resonance imaging.pdf | 190.78 MB | Adobe PDF |
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