What mathematical process is used in MRI image reconstruction?

The process used in MRI image reconstruction is the Fourier Transform. This mathematical tool is crucial for converting the raw data obtained from MRI scans, which is typically in the frequency domain, into a coherent image that is spatially meaningful. MRI acquires signals that contain information about the spatial frequencies of the image, and the Fourier Transform allows for the reconstruction of an image by transforming these signals from the frequency domain back to the spatial domain. This is essential to visualize the anatomical structures and pathologies within the body.

While techniques like Gradient Descent, Wavelet Transform, and Eigenvalue Decomposition play significant roles in various areas of mathematics and image processing, they are not the primary mathematical method used for the purpose of reconstructing MRI images from raw data. Fourier Transform specifically addresses the needs of MRI imaging, making it a foundational element of the technology.