The Moner framework, which currently focuses on radial MRI, can be extended to accommodate diverse MRI sampling patterns like Cartesian and spiral by modifying its underlying mathematical formulations and optimization strategies.
Adaptation of the Forward Model: The Fourier-slice theorem, which is central to Moner's current formulation, is specific to radial sampling. To extend Moner to Cartesian sampling, the framework can utilize the 2D Fourier transform directly, allowing for the reconstruction of images from Cartesian k-space data. For spiral sampling, the framework would need to incorporate a spiral trajectory model, which can be achieved by adjusting the projection data generation process to account for the non-linear sampling paths.
Reformulation of the Optimization Pipeline: The optimization pipeline can be adapted to handle the different characteristics of Cartesian and spiral data. For instance, the integral projection model used in Moner can be modified to reflect the specific sampling geometry of these patterns, ensuring that the optimization process remains stable and effective.
Incorporation of Motion Models: The motion model currently employed in Moner can also be generalized to account for the unique motion artifacts associated with different sampling patterns. This may involve developing new motion estimation techniques that are tailored to the specific dynamics of Cartesian and spiral acquisitions.
Training and Evaluation: Finally, extensive training and evaluation on datasets that include various sampling patterns will be essential. This will help in fine-tuning the model parameters and ensuring that the Moner framework generalizes well across different MRI acquisition protocols.