Comparison of the proposed method, standard L+S, GRASP and XD-GRASP reconstructions in terms of optimization method, gridding technique, and reconstruction time for Dataset-2 for different AFs.

The proposed method shows improved reconstruction efficiency compared to L+S, GRASP and XD-GRASP reconstruction due to the addition of SC-GROG gridding and MFISTA-VA based optimization in standard L+S reconstruction.

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Bibliographic Details
Main Author:	Faisal Najeeb (20542714) (author)
Other Authors:	Kashif Amjad (7665488) (author), Irfan Ullah (847820) (author), Hammad Omer (17412783) (author)
Published:	2025
Subjects:	Cell Biology Physiology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Chemical Sciences not elsewhere classified Physical Sciences not elsewhere classified Information Systems not elsewhere classified rank plus sparse nonlinear conjugate gradient high computational burden div >< p arterial signal intensity repeated nufft gridding radial sampling pattern multiple sparsity constraints convergence analysis shows improved temporal resolution e ., grasp reconstructing dynamic contrast dce mr images coil mri data reconstruction time due highly accelerated free grasp reconstruction technique mri reconstruction techniques angle radial data radial data dynamic contrast reconstruction time sparsity transform radial dce grog gridding convergence error mri reconstruction temporal incoherence accelerated golden reconstruction results grasp include grasp ). parallel mri mri datasets mri ). vivo dce variable acceleration selected region results show proposed method paper introduces optimization problem optimal solution novel approach monotone fista method combines mean values major limitations contemporary method compressed sensing cartesian grid address limitations acceleration capability
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Comparison of the proposed method, standard <i>L+S</i>, GRASP and XD-GRASP reconstructions in terms of optimization method, gridding technique, and reconstruction time for Dataset-2 for different AFs.

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