Medical imaging plays a critical role in various clinical applications. However, due to multiple considerations such as cost and radiation dose, the acquisition of certain image modalities may be limited. Thus, medical image synthesis can be of great benefit by estimating a desired imaging modality without incurring an actual scan. In this paper, we propose a generative adversarial approach to address this challenging problem. Specifically, we train a fully convolutional network (FCN) to generate a target image given a source image. To better model a nonlinear mapping from source to target and to produce more realistic target images, we propose to use the adversarial learning strategy to better model the FCN. Moreover, the FCN is designed to incorporate an image-gradient-difference-based loss function to avoid generating blurry target images. Long-term residual unit is also explored to help the training of the network. We further apply Auto-Context Model to implement a context-aware deep convolutional adversarial network. Experimental results show that our method is accurate and robust for synthesizing target images from the corresponding source images. In particular, we evaluate our method on three datasets, to address the tasks of generating CT from MRI and generating 7T MRI from 3T MRI images. Our method outperforms the state-of-the-art methods under comparison in all datasets and tasks.

Medical Image Synthesis with Deep Convolutional Adversarial Networks

https://pure.uva.nl/ws/files/2440559/151770_430596.pdf

Quantifying inter-individual anatomical variability in the subcortex using 7 T structural MRI

Over 20?000 MR systems are currently installed worldwide and, although the majority operate at magnetic fields of 1.5?T and below (i.e. about 70%), experience with 3-T (in high-field clinical diagnostic imaging and research) and 7-T (research only) human MR scanners points to a future in functional and metabolic MR diagnostics. Complementary to previous studies, this review attempts to provide an overview of ultrahigh-field MR research with special emphasis on emerging clinical applications at 7?T. We provide a short summary of the technical development and the current status of installed MR systems. The advantages and challenges of ultrahigh-field MRI and MRS are discussed with special emphasis on radiofrequency inhomogeneity, relaxation times, signal-to-noise improvements, susceptibility effects, chemical shifts, specific absorption rate and other safety issues. In terms of applications, we focus on the topics most likely to gain significantly from 7-T MR, i.e. brain imaging and spectroscopy and musculoskeletal imaging, but also body imaging, which is particularly challenging. Examples are given to demonstrate the advantages of susceptibility-weighted imaging, time-of-flight MR angiography, high-resolution functional MRI, 1H and 31P MRSI in the human brain, sodium and functional imaging of cartilage and the first results (and artefacts) using an eight-channel body array, suggesting future areas of research that should be intensified in order to fully explore the potential of 7-T MR systems for use in clinical diagnosis. Copyright (C) 2011 John Wiley & Sons, Ltd. (Less)

/pdf/7-t-mr-from-research-to-clinical-applications-3tstzcbwkt.pdf

7-T MR—from research to clinical applications?

https://cyberleninka.org/article/n/690828.pdf

Key clinical benefits of neuroimaging at 7T.

The aging brain undergoes several anatomical changes that can be measured with Magnetic Resonance Imaging (MRI). Early studies using lower field strengths have assessed changes in tissue properties mainly qualitatively, using [Formula: see text]- or [Formula: see text]- weighted images to provide image contrast. With the development of higher field strengths (7 T and above) and more advanced MRI contrasts, quantitative measures can be acquired even of small subcortical structures. This study investigates volumetric, spatial, and quantitative MRI parameter changes associated with healthy aging in a range of subcortical nuclei, including the basal ganglia, red nucleus, and the periaqueductal grey. The results show that aging has a heterogenous effects across regions. Across the subcortical areas an increase of [Formula: see text] values is observed, most likely indicating a loss of myelin. Only for a number of areas, a decrease of [Formula: see text] and increase of QSM is found, indicating an increase of iron. Aging also results in a location shift for a number of structures indicating the need for visualization of the anatomy of individual brains.

/pdf/effects-of-aging-on-t1-t2-and-qsm-mri-values-in-the-2ua271rssg.pdf

Effects of aging on T1, T2*, and QSM MRI values in the subcortex

Clinical fMRI: Evidence for a 7 T benefit over 3 T

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Clinical fMRI: Evidence for a 7 T benefit over 3 T