Noise-reduction techniques for 1H-FID-MRSI at 14.1 T: Monte Carlo validation and in vivo application

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Low-light photography produces images with low signal-to-noise ratios due to limited photons. In such conditions, common approximations like the Gaussian noise model fall short, and many denoising techniques fail to remove noise effectively. Although deep- ...

Purpose: Although clinical 7T MRI offers various advantages compared to lower field strengths, achieving spatially uniform flip angle distributions remains a challenge. Sampling Perfection with Application optimized Contrast using different flip angle Evol ...

Recently, the R2D2 paradigm, standing for ‘Residual-to-Residual DNN series for high-Dynamic-range imaging’, was introduced for image formation in Radio Interferometry (RI) as a learned version of the traditional algorithm CLEAN. The first incarnations of R ...

Introduction Type C hepatic encephalopathy (HE) is a decompensating event of chronic liver disease leading to severe motor and cognitive impairment. The progression of type C HE is associated with changes in brain metabolite concentrations measured by 1H m ...

Using compressed sensing (CS), stepped Raman optical frequency-domain reflectometry (ROFDR) can be performed on a reduced set of frequencies. We experimentally show that temperature hotspots can be reconstructed from a small subset of the usually required ...

Noise-reduction techniques for 1H-FID-MRSI at 14.1 T: Monte Carlo validation and in vivo application

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Dark Noise Diffusion: Noise Synthesis for Low-Light Image Denoising

Individually optimized dynamic parallel transmit pulses for 3D high‐resolution SPACE imaging at 7T

S-R2D2: a spherical extension of the R2D2 deep neural network series paradigm for wide-field radio-interferometric imaging

Diffusion of brain metabolites highlights altered brain microstructure in type C hepatic encephalopathy: a 9.4 T preliminary study

Compressed Sensing for Temperature Measurements With Incoherent Raman OFDR Distributed Sensors