[lostlogin]

> "Default MRI" (i.e. fully sampled) should definitely be acquired when possible when testing

It seems unlikely you wouldn’t appreciate this already, but clinical MRI has not fully sampled in a long time. Between the old and the new - reduced phase resolution (image plane and slice plane) parallel imaging, compressed sense (or sensing), reduced frequency resolution with partial echo techniques, high reconstruction max trim with low acquisition matrix, the list is quite long.

The changes in resulting artefacts as acceleration techniques change (eg high compressed sense values) is a bit of a change to how people work. Very digital looking artefacts are just gross.

Thanks for your work! We need more speed.

[notarandomer]

Thanks for the comment! You're right, I was oversimplifying saying that default MRI would be fully sampled. My main point still stands, you can't just chuck ML onto current protocols to do a direct comparison with ML and more conventional reconstruction methods to give clinicians access to both and expect an improvement (beyond potentially denoising) because the conventional scans are already very good at what they do. Where ML can help is in cases where we can't produce conventional scans (e.g. with very short scan times or high temporal resolution).

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Those striving for shorter scan times (eg functional) go to such massive lengths that it blew my mind when I encountered it on a research magnet. Every millisecond counted.

Watching the mental gymnastics used to deal with multi band/simultaneous multi slice (or whatever vendors call it) with functional MRI was impressive to me.

Using ML to work out voxel results in such low spacial resolution scans has got to be scary.