https://www.selleckchem.com/products/abbv-cls-484.html 3D stack-of-spirals MRF was successfully applied for whole brain quantitative T1 and T2 at 0.55T, with spatial resolution of 1.2mm×1.2mm×5mm, and acquisition time of 8.5min. Moreover, the T1 and T2 quantifications had precision <5%, despite the lower SNR of 0.55T. A 3D whole-brain stack-of-spirals FISP MRF sequence is feasible for T1 and T2 mapping at 0.55T. A 3D whole-brain stack-of-spirals FISP MRF sequence is feasible for T1 and T2 mapping at 0.55 T.We study two state of the art deep generative networks, the Introspective Variational Autoencoder and the Style-Based Generative Adversarial Network, for the generation of new diffusion-weighted magnetic resonance images. We show that high quality, diverse and realistic-looking images, as evaluated by external neuroradiologists blinded to the whole study, can be synthesized using these deep generative models. We evaluate diverse metrics with respect to quality and diversity of the generated synthetic brain images. These findings show that generative models could qualify as a method for data augmentation in the medical field, where access to large image database is in many aspects restricted. Superficial fibromatosis exhibits variable MR signal intensity due to collagenous and fibroproliferative components. Quantifying this signal heterogeneity using image texture analysis and T2-mapping could have prognostic and therapeutic implications. This IRB-approved retrospective study included 13 patients with superficial fibromatosis, managed by observation, electron beam radiotherapy (EBT), or pentoxifylline/vitamin E. Two-dimensional regions of interest (ROIs) were drawn on proton-density or T2-weighted MRI for radiomics feature analysis, and corresponding T2-maps. Comparisons were made between baseline and follow-up T2 relaxation times and radiomics features Shannon's entropy, kurtosis, skewness, mean of positive pixels (MPP), and uniformity of distribution of positive