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Found 4 papers, 2 papers with code
ATOMMIC: An Advanced Toolbox for Multitask Medical Imaging Consistency to facilitate Artificial Intelligence applications from acquisition to analysis in Magnetic Resonance Imaging
We benchmark 25 DL models on eight publicly available datasets to present distinct applications of ATOMMIC on accelerated MRI reconstruction, image segmentation, quantitative parameter map estimation, and joint accelerated MRI reconstruction and image segmentation utilizing MTL.
Deep Learning-based Intraoperative MRI Reconstruction
Results: The DL reconstruction was strongly favored or favored over the CS reconstruction for 33/40, 39/40, and 8/40 of cases for reader 1, 2, and 3, respectively.
A Densely Interconnected Network for Deep Learning Accelerated MRI
In an ablation study, the individual architectural modifications all contributed to this improvement, by reducing the SSIM and NMSE with approximately 3% and 5% for four-fold acceleration, respectively.
Reconstructing unseen modalities and pathology with an efficient Recurrent Inference Machine
The IndRNN is an efficient recurrent unit, reducing inference time by 68\% compared to CS, whereas maintaining performance.
