Most impressively, when we ran automated amygdala segmentation on the real 3T and synthetic 7T, the segmentations from the synthetic 7T better matched manual segmentations of the amygdala!!

Our models outperform existing models on this task in terms of traditional metrics. However, a set of four blinded radiologists and MRI professionals also subjectively rated the synthetic images to be of higher visual quality than the images they were synthesized from.

Shockingly, when applied to unseen 3T scans, our models produce synthetic scans that resemble the original images, but sharper and with better contrast, while avoiding common artifacts seen on 7T scans.

We exploited a valuable dataset of 172 cognitively impaired and unimpaired older people from
@biofinder.bsky.social with paired 3T and a 7T T1-weighted scans. To this dataset, we apply our own specialized U-Net and GAN U-Net model, as well as some previously described models.

‼️NEW PREPRINT‼️

What if you could take a normal 3T T1w MRI and make it look like it was acquired from a 7T scanner?

That's exactly what we do using AI in our new preprint!

Link: arxiv.org/abs/2507.13782

#neuroskyence #neurosky #compneuro #AI #datascience #neurology #mrisky #neuroimaging