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. 2020 Jul 14;296(3):627–637. doi: 10.1148/radiol.2020192793

Figure 2b:

Graphs show image quality metrics of relative cerebral blood flow change (rΔCBF) maps from PET-plus-MRI model, MRI-only model, and rΔCBF measured with multidelay arterial spine labeling (ASL rΔCBF) compared with reference PET. (a) Patients with Moyamoya disease. (b) Healthy control participants. In patients with Moyamoya disease, both deep learning models were better than was ASL rΔCBF on all three metrics. In healthy control participants, PET-plus-MRI model was better than was ASL rΔCBF in all three metrics, while MRI-only model was only better than was ASL rΔCBF for structural similarity index (SSIM). There was no difference between two models in all metrics in both patients with Moyamoya disease and healthy control participants. PSNR = peak signal-to-noise ratio, RMSE = root mean square error.

Graphs show image quality metrics of relative cerebral blood flow change (rΔCBF) maps from PET-plus-MRI model, MRI-only model, and rΔCBF measured with multidelay arterial spine labeling (ASL rΔCBF) compared with reference PET. (a) Patients with Moyamoya disease. (b) Healthy control participants. In patients with Moyamoya disease, both deep learning models were better than was ASL rΔCBF on all three metrics. In healthy control participants, PET-plus-MRI model was better than was ASL rΔCBF in all three metrics, while MRI-only model was only better than was ASL rΔCBF for structural similarity index (SSIM). There was no difference between two models in all metrics in both patients with Moyamoya disease and healthy control participants. PSNR = peak signal-to-noise ratio, RMSE = root mean square error.