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ISMRM 2023 presentation - June 2023 Full abstract is available here: https://www.researchgate.net/publicat... Code of this project is available as part of the NCC1701 project: https://github.com/soumickmj/NCC1701 PyTorch Complex package is available here: https://github.com/soumickmj/pytorch-... Synopsis: Iterative undersampled MRI reconstructions, such as compressed sensing, can reconstruct undersampled MRIs - but due to their slow execution speed, they are not suitable for real-time applications. Several deep learning approaches have been proposed, mostly working in image space. Some of the approaches, which work on the k-space or in a mix of spaces, employ real-valued convolutions splitting the complex k-space into real and imaginary parts for processing - destroying the geometric relationship within the data. This research proposes Fourier-PD and Fourier-PDUNet models using complex-valued convolutions, which attempt to predict missing k-space frequencies and also to reduce artefacts in the image space. To see all my publications: https://scholar.google.com/citations?... LinkedIn: / soumick ResearchGate: https://www.researchgate.net/profile/... Twitter: soumick1993