This project involved developing MATLAB scripts for simulating and visualizing MRI k-space data, focusing on transforming k-space data into images, analyzing signal-to-noise ratios (SNR), and adjusting image resolution through k-space modifications. We explored artifacts such as aliasing in MRI images resulting from field-of-view adjustments, highlighting the practical aspects of sampling theory in MRI imaging. Additionally, we applied CT image reconstruction techniques, including sinogram generation, Radon transform analysis, and filtered back-projection methods, to enhance image resolution and quality from parallel beam projections
If you would like to learn more about this project, a comprehensive report is available below.