vitorsr on Machine Learning for MRI Image Reconstruction

Comment on Machine Learning for MRI Image Reconstruction

Though compressed sensing can improve the image quality relative to a vanilla inverse Fourier transform, it still suffers from artifacts.

Odd remark. FDA approves compressed sensing products (e.g., [1], [2], [3], [4]) precisely because it is possible (and provably so) to quantify and/or characterize such “artifacts” up to substantial equivalence.

[1] https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn...

[2] https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn...

[3] https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn...

[4] https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn...

bick_nyers 4y

This is actually quite interesting and currently relevant to me, thanks for sharing

vitorsr 4y

The following query might also interest you then:

    "510(k)" "deep learning" site:accessdata.fda.gov/cdrh_docs

Or alternatively replace "deep learning" by either another distinctive theory/methodology employed or trade/device name.

I do remind you to cross-check what material product is being reviewed.

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