Fig. 1: Fine-tuning of LF-SynthSR and overall imaging analysis pipeline and performance.

a The architecture of the convolutional neural network LF-SynthSR (v2). b The overall imaging analysis pipeline includes acquisition of LF-MRI images at different contrasts and resolutions, super-resolving the raw images with LF-SynthSR followed by segmentation using SynthSeg. c–h LF-MRI images were prepared with the original (v1, T1 + T2 AXI) or fine-tuned (v2, T1 and T2 AXI) LF-SynthSR followed by automated segmentation with SynthSeg. LF-MRI segmentation volumes for the hippocampus (c and f), lateral ventricles (d and g) and whole brain (e and h) were compared with volumes derived from 1 mm MP-RAGE images acquired at high-field using the absolute symmetrized percentage difference (ASPD) and Dice coefficient. The ASPD for hippocampus (T1w p = 0.027; T2w p = 0.014) and lateral ventricle volumes (p < 0.001 for T1w and T2w) relative to high-field was less for T1w or T2w LF-MRI inputs when LF-SynthSR v2 was used. The ASPD for whole brain was improved for T1w (p < 0.001) but not for T2w (p = 0.040) when using LF-SynthSR v2. The Dice coefficient for the hippocampus was more accurate when v2 was used for both T1w (p = 0.022) and T2w inputs (p < 0.001), similar for lateral ventricles, and lower for the whole brain (p < 0.001). For each subpanel, the box plots show the median, the interquartile range, and the Tukey whiskers. Each box plot corresponds to n = 20 biological replicates. Source data is available via the following link: https://doi.org/10.7910/DVN/9PANMC. AXI, axial; LF, low-field; T1w, T1 weighted; T2w, T2 weighted. * p < 0.05, ** p < 0.01 using the Wilcoxon signed rank test compared to v1.