6.556J Data Acquisition and Image Reconstruction in MRI
Applies analysis of signals and noise in linear systems, sampling, and Fourier properties to magnetic resonance (MR) imaging acquisition and reconstruction. Provides adequate foundation for MR physics to enable study of RF excitation design, efficient Fourier sampling, parallel encoding, reconstruction of non-uniformly sampled data, and the impact of hardware imperfections on reconstruction performance. Surveys active areas of MR research. Assignments include Matlab-based work with real data. Includes visit to a scan site for human MR studies.
This class has 6.011 as a prerequisite.
6.556J will be offered this semester (Fall 2018). It is instructed by E. Adalsteinsson.
This class counts for a total of 12 credits. This is a graduate-level class.
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