[ska]

The point I was trying to make has nothing to do with image quality.

The issue was, radiologist had to deal with a choice of different post-processing of this data. The processing they said they liked best (somewhat consistently) was not the processing that they performed best on, empirically (somewhat consistently).

This is related to the issue of evaluating the value of ML post processing, we could see a similar effect there. After all one school of thought was that preference was in some sense driving by familiarity rather than what they were actually able to discriminate.

FWIW IQ evaluation in MRI is a somewhat problematic thing anyway, but acceleration certainly tends to make it worse in some ways. It's not obvious how effective various mitigation approaches are.

[lostlogin]

Thanks - I missed your point. Image quality in MR is very much a moving target too as it varies between patients and there is a far bit of variation in practice. Scans are speed up or slowed down for a variety of reasons. Making a scan faster to fit in another patient or any number of other reasons is something that happens regularly.