T1 mapping and image reconstruction: examination for quantitative MRI

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Date
2021-05-11
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Johns Hopkins University
Abstract
Magnetic resonance imaging (MRI) is a major imaging modality widely used in medical practice. Compared to other medical imaging techniques, MRI has several advantages such as non-invasiveness, high tissue contrast, additional information, etc. While most other imaging techniques directly generate medical images, a special characteristic of MRI is that raw data are acquired in the k-space, an extension of the Fourier space, which represents spatial frequency information. Therefore, reconstruction algorithms are needed to convert collected raw data to human-readable images of the scanned region. Quantitative MRI refers to MRI techniques that map meaningful properties of tissues. Amongst other tissue-specific parameters, we are particularly interested in those related to relaxation, i.e., the process of protons returning to the original state from an excited state. There are two relaxation mechanisms in MRI, namely transverse relaxation and longitudinal relaxation, concerned with the transverse and longitudinal components of net magnetization of protons, respectively. This thesis consists of three parts. Firstly, we introduce hardware and fundamental principles of MRI. In the second part, we define three tissue-specific parameters related to relaxation—T1 (for longitudinal relaxation), T2 (for transverse relaxation) and T2* (for reduced transverse relaxation). In particular, we focus on T1 and present several commonly used T1 mapping methods for calculating T1 values, such as the dual-flip-angle (DFA) method. The last part of the thesis serves as a tutorial that introduces several basic steps that reconstruct an image from acquired raw data.
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Quantitative MRI, T1 mapping, image reconstruction, DFA, IR
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