ADMM-Net: A Deep Learning Approach for Compressive Sensing MRI — mentioned by lp251

Wed, 28 Nov 2018 18:02:11 GMT

The former. It is known that we can reconstruct MR images at full fidelity- with no loss of information- by randomly sampling "k-space" at something like 10% of the usual sampling rate. This leads to much faster acquisitions. I believe Siemens has a product based on this technology that is currently going to market- https://usa.healthcare.siemens.com/magnetic-resonance-imagin... One issue, though, is that truly random sampling isn't great from a practical point of view. Sampling patterns are constrained by other equipment considerations. There is also the issue of noise. Machine learning for…

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ADMM-Net: A Deep Learning Approach for Compressive Sensing MRI · HackerPapers discussions

ADMM-Net: A Deep Learning Approach for Compressive Sensing MRI — mentioned by lp251